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A. Editorships (books/special issues)
1.
Magoulas G.D., Investigations into Living
Systems, Artificial Life, and Real-World Solutions, IGI
Global, 2013.
2.
Magoulas G.D., E-Infrastructures and Technologies for Lifelong
Learning, IGI Global, 2011.
3.
Magoulas G.D. Artificial Intelligence Tools in Human–Computer
Interaction, special issue of the International Journal on Artificial Intelligence
Tools, vol.19(6), December 2010, pp. 713-715.
4.
Roussos G., Musolesi M., Magoulas G.D., Human Behaviour in Ubiquitous Environments: Modeling of Human Mobility Patterns, special issue of Pervasive
and Mobile Computing Journal, vol. 6(4), August 2010, pp.
399-400.
5. Roussos G., Musolesi
M., Magoulas G.D, Human Behavior in
Ubiquitous Environments: Experience and interaction design, special issue of Pervasive and Mobile Computing, vol. 6(5), October 2010, pp. 497-498.
6. Magoulas G.D., and Dounias G., Computational Intelligence in
Medicine and Biology, special issue of the journal
Applied Intelligence: The
International Journal of Artificial Intelligence, Neural Networks, and Complex
Problem-Solving Technologies, vol. 27(3), December, 2007 pp.
189-192.
7. Magoulas G. D., and Ghinea G., Intelligence-based
Adaptation for Ubiquitous Multimedia Communications, special
issue of the Journal of Network
and Computer Applications, vol. 30(3), August 2007, pp.
955-1083.
8. Magoulas G.D., Lepouras G, and
Vassilakis C., Virtual Reality in the e-Society,
special Issue of the journal Virtual Reality,
vol. 11(2-3), June, 2007, pp. 71-184.
9. Magoulas G.D, and Chen Y., Human Factors in
Personalised Systems and Services, special
issue of the journal Interacting with
Computers, vol. 18(3), May 2006, pp 327-506.
10. Magoulas G.D, and Chen S., Advances
in Web-based Education: Personalized Learning Environments, Information Science
Publishing, 2006 (ISBN: 1-59140-691-9).
11. Magoulas G.D., and Dounias G., Intelligent
Technologies in Bioinformatics and Medicine, special issue of
the journal Computers in
Biology and Medicine, vol. 36(10), October 2006, pp.
1045-1184.
12. Magoulas G.D., Dounias G. Linkens
D.A., Intelligent Tools for Problem Solving
in Bioinformatics and Medicine, special issue of the International
Journal of Artificial Intelligence Tools, vol. 15(3), June
2006, pp. 331-432.
13. Chen S., and Magoulas G.D., Adaptable and
Adaptive Hypermedia Systems, IRM Press,
2005 (ISBN: 1-59140-567-X).
14. Dounias G., Magoulas G. and Linkens
D., Intelligent Technologies in Bioinformatics and Medicine (Workshop
Proceedings) Published by the Univ. of the Aegean and the European Network on
Intelligent Technologies (EUNITE) for Smart Adaptive Systems, 2004 (ISBN:
960-7475-28-3).
Home - Teaching - Publications - Bio - Blog - Department
B. Journal papers
1.
Papanikolaou K.A., Makrh K., Magoulas G.D.,
Chinou D., Georgalas A., Roussos P., Synthesizing Technological and Pedagogical
Knowledge in Learning Design: a Case Study in Teacher Training on Technology
Enhanced Learning, International Journal of Digital Literacy and Digital
Competence, forthcoming.
2.
Sikora T., Magoulas G.D., Evolutionary
Approaches to Signal Decomposition in an Application Service Management System,
Soft Computing, forthcoming.
3. Cocea M. and Magoulas G.D., Participatory
Learner Modelling Design: a Methodology for Iterative Learner Models
Development, Information Sciences, 321, 48–70, 2015.
4. Adam S.P., Karras D.A., Magoulas
G.D., Vrahatis M.N, Solving the linear
interval tolerance problem for weight initialization of neural networks,
Neural Networks, 54, 17–37, 2014.
5. Sikora T., Magoulas G.D. Neural adaptive
control in application service management environment, Evolving
Systems, 4(4), 267-287, 2013.
6. Laurillard, D., Charlton, P., Craft,
B., Dimakopoulos, D., Ljubojevic, D., Magoulas, G., Masterman, E., Pujadas, R.,
Whitley, E.A., Whittlestone, K., A constructionist learning
environment for teachers to model learning designs, Journal of
Computer Assisted Learning, 29(1), 15–30, 2013.
7. Gutierrez-Santos S., Mavrikis M.,
and Magoulas G.D., A Separation of
Concerns for Engineering Intelligent Support for Exploratory Learning
Environments, Journal of Research and Practice in Information
Technology, 44(3), 347-360, 2012.
8. Charlton P., Magoulas G. and
Laurillard D., Enabling Creative
Learning Design through Semantic Technologies, Technology,
Pedagogy and Education, 21(2), 231-253, 2012.
9. Cocea M., Magoulas G.D., User
Behaviour-driven Group Formation through Case-based Reasoning and Clustering,
Expert Systems with Applications, 39(10), 8756-8768, 2012.
10. Noss R., Poulovassilis A., Geraniou
E., Gutierrez-Santos S., Hoyles C., Kahn K., Magoulas G.D., Mavrikis M., The design of a
system to support exploratory learning of algebraic generalisation,
Computers and Education, 59(1), 63–81, 2012.
11. Peng C.-C. and Magoulas G.D., Nonmonotone
Levenberg-Marquardt Training of Recurrent Neural Architectures for Processing
Symbolic Sequences, Neural Computing & Applications, 20(6),
897-908, 2011.
12. Peng C.-C. and
Magoulas G.D., Nonmonotone
BFGS-trained Recurrent Neural Networks for Temporal Sequence Processing,
Applied Mathematics and Computation, 217(12), 5421-5441, 2011.
13. de Freitas
S., Rebolledo-Mendez G., Liarokapis F., Magoulas G., Poulovassilis A., Learning as immersive
experiences: Using the four-dimensional framework for designing and evaluating
immersive learning experiences in a virtual world, British Journal of
Educational Technology, 41(1), 69-85, 2010.
14. Cocea M., Magoulas G.D., Hybrid
Model for Learner Modelling and Feedback Prioritisation in Exploratory
Learning, International Journal of Hybrid Intelligent Systems, 6(4), 211-230,
2009.
15. Dimakopoulos D.N. and Magoulas G.
D., Interface design
and evaluation of a personal information space for mobile learners,
International Journal of Mobile Learning and Organisation, vol.3(4), 440 –
463, 2009.
16. Peng C.-C. and
Magoulas G.D., Advanced Adaptive Nonmonotone Conjugate Gradient Training
Algorithm for Recurrent Neural Networks, International Journal of Artificial
Intelligence Tools, vol. 17(5), 963-984, 2008.
17. Anastasiadis A.D., Magoulas G.D., Particle Swarms and
Nonextensive Statistics for Nonlinear Optimisation, The Open Cybernetics and Systemics
Journal, vol. 2, 173-179, 2008.
18. de Freitas S., Harrison I., Magoulas
G.D., Mee A., Mohamad F., Oliver M., Papamarkos G., Poulovassilis A., The Development of
a System for Supporting the Lifelong Learner, British Journal of Educational
Technology, 37(6), pp 867-880, 2006.
19. O'Neill P.D., Magoulas G.D., Liu X. Applying
Wave Processing Techniques to Clustering of Gene Expressions,
Journal of Intelligent Systems, vol. 15(1-4), 107–128, 2006.
20. Anastasiadis A. and Magoulas G.D., Analysing the
Localisation Sites of Proteins through Neural Networks Ensembles,
Neural Computing & Applications, vol. 15(3), 277 – 288, 2006.
21. Anastasiadis A., Magoulas G.D., and
Vrahatis M.N, Improved sign-based learning algorithm derived by the composite
nonlinear Jacobi process, Journal of Computational and Applied Mathematics,
vol. 191, 166 – 178, 2006.
22. Anastasiadis A. and Magoulas G.D., Evolving Stochastic
Learning Algorithm based on Tsallis Entropic index, The
European Physical Journal B, vol. 50, 277–283, 2006.
23. Frias-Martinez E., Magoulas G. D.,
Chen S. Y., Macredie R. D., Automated User
Modeling for Personalized Digital Libraries, International
Journal of Information Management, vol. 26(3), 179-260, 2006.
24. Magoulas G.D., Anastasiadis A.D., Approaches to
Adaptive Stochastic Search Based on the Nonextensive q-Distribution,
International Journal of Bifurcation and Chaos, Vol. 16, No. 7, 2081-2091,
2006.
25. Magoulas G. D., Neuronal networks
and textural descriptors for automated tissue classification in endoscopy,
Oncology Reports, vol. 15, 997-1000, 2006.
26. Magoulas G. and Vrahatis M.N., Adaptive Algorithms
for Neural Network Supervised Learning: A Deterministic Optimization Approach,
International Journal of Bifurcation and Chaos, vol. 16(7), 1929–1950, 2006.
27. Plagianakos, V. P., Magoulas G. D.
and Vrahatis M. N., Evolutionary
training of hardware realizable
multilayer perceptrons, Neural Computing & Applications, vol. 15(1), 33-40, 2006.
28. Plagianakos, V. P., Magoulas G. D.
and Vrahatis M. N., Distributed
Computing Methodology for Training Neural Networks in an Image-guided
Diagnostic Application, Computer Methods and Programs in
Biomedicine, vol. 81(3), 228-235, 2006.
29. Anastasiadis A., Magoulas G.D., and
Vrahatis M.N., New Globally
Convergent Training Scheme Based on the Resilient Propagation Algorithm,
Neurocomputing, vol. 64, 253-270, March, 2005.
30. Anastasiadis A., Magoulas G. D., and
Vrahatis M.N, Sign-based Learning
Schemes for Pattern Classification, Pattern Recognition
Letters, vol. 26, 1926–1936, 2005.
31. Chen S.Y., Magoulas G.D., and
Dimakopoulos D., A Flexible Interface Design for Web
Directories to Accommodate Different Cognitive Styles,
Journal of the American Society for Information Science and Technology, vol.
56(1), 70-83, 2005.
32. Frias-Martinez E., Magoulas G., Chen
S., Macredie R. , Modeling
Human Behavior in User-Adaptive Systems: Recent Advances Using Soft Computing
Techniques, Expert Systems with Applications, vol. 29(2),
320–329, 2005.
33. Ghinea G., Magoulas G.D., and
Siamitros C., Multi-criteria
Decision Making for Enhanced Perception-based Multimedia Communication,
IEEE Tr. Systems, Man and Cybernetics: part A, vol.
35(6), 855-866, 2005.
34. Ghinea G., Magoulas G.D., and
Siamitros C., Intelligent
Synthesis Mechanism for Deriving Streaming Priorities of Multimedia Content,
IEEE Tr. Multimedia, vol. 7(6), 1047-1053, 2005.
35. Ghinea G., Thomas J. P., Magoulas
G.D., and Heravi S., Adaptation as a premise for perceptual-based multimedia
communications, Int. J. Information Technology and Management, vol. 4(4),
405-422, 2005.
36. Stathacopoulou R., Magoulas G. D.,
Grigoriadou M. and Samarakou M., Neuro-fuzzy knowledge
processing in intelligent learning environments for improved student diagnosis,
Information Sciences, vol. 170(2), 273-307, 2005.
37. Anastasiadis A., and Magoulas G.D., Nonextensive statistical
mechanics for hybrid learning of neural networks, Physica A:
Statistical Mechanics and its Applications, vol. 344, 372-382, 2004.
38. Chen S., Magoulas G.D. and Macredie
R. Cognitive
Styles and Users’ Reponses to Structured Information Representation,
International Journal on Digital Libraries, vol. 4(2), 93-107, 2004.
39. Ghinea G., Magoulas G. D. and Frank
A.O. Intelligent
protocol adaptation in a medical e-collaboration environment,
International Journal of Artificial Intelligence Tools, Vol. 13(1), 199-218,
2004.
40. Ghinea G., Magoulas G. D., and Frank
A. O., Intelligent Multimedia
Communication for Enhanced Medical e-Collaboration in Back Pain Treatment,
Transactions of Institute Measurement Control, vol. 26(3), 223-244, 2004.
41. Magoulas G.D., Karkanis S.A., Karras
D.A. and Vrahatis M.N., Evaluation of texture-based schemes in neural
classifiers training, WSEAS Transactions on Computers, vol. 3(6), 1729-1735,
December 2004.
42. Magoulas G.D., Plagianakos V.P., and
Vrahatis M.N., Neural Network-based
Colonoscopic Diagnosis Using On-line Learning and Differential Evolution,
Applied Soft Computing, Vol. 4(4), 369-379, 2004.
43. Hossain S., Pouloudi A., Magoulas
G.D. and Grigoriadou M., IT Adoption in British and
Greek Secondary Education: Issues and Reflections, Themes in Education, vol.
4(2), 123-154, 2003.
44. Magoulas G.D., Papanikolaou K.A.,
and Grigoriadou M., Adaptive web-based learning:
accommodating individual differences through system’s adaptation,
British Journal of Educational Technology, vol. 34(4), 511 – 527, 2003.
45. O’Neill P., Magoulas G. D., and Liu
X., Improved Processing of
Microarray Data using Image Reconstruction Techniques, IEEE
Tr. Nanobioscience, vol. 2(4), 176-183, 2003.
46. Papanikolaou K., Grigoriadou M.,
Kornilakis H., and Magoulas G.D., Personalising the Interaction in a Web-based
Educational Hypermedia System: the case of INSPIRE,
User-Modeling and User-Adapted Interaction, vol. 13, 213-267, 2003.
47. Vrahatis M.N., Magoulas G.D. and
Plagianakos V.P., From linear to nonlinear iterative methods,
Applied Numerical Mathematics, vol. 45(1), 59 - 77, 2003.
48. Magoulas G.D., Plagianakos V.P., and
Vrahatis M.N., Globally convergent algorithms with
local learning rates, IEEE Tr. Neural Networks, vol. 13(3),
774-779, 2002.
49. Papanikolaou K., Grigoriadou M.,
Magoulas G.D., and Kornilakis H., Towards New Forms
of Knowledge Communication: the Adaptive Dimension of a Web-based Learning
Environment, Computers and Education, vol. 39,
333-360, 2002.
50. Plagianakos V. P., Magoulas G.D.,
and Vrahatis M.N., Deterministic
Nonmonotone Strategies for Effective Training of Multi-layer Perceptrons,
IEEE Tr. Neural Networks, vol. 13(6), 1268-1284, 2002.
51. Magoulas G.D. , Papanikolaou K.A.,
and Grigoriadou M. Neurofuzzy
Synergism for Planning the Content in a Web-based Course,
Informatica, vol. 25, 39-48, 2001.
52. Magoulas G.D., Plagianakos G.D.,
Androulakis G.S. and Vrahatis M.N., A Framework for the Development of
Globally Convergent Adaptive Learning Rate Algorithms,
International Journal of Computer Research, vol. 10(1), 1-10, 2001.
53. Magoulas G.D., Plagianakos V.P. and
Vrahatis M.N., Adaptive stepsize algorithms for
on-line training of neural networks, Nonlinear Analysis:
Theory, Methods and Applications, vol. 47, 3425-3430, 2001.
54. Parsopoulos K.E. ,
Plagianakos V.P. , Magoulas G.D. and Vrahatis M.N., Objective function
``stretching’’ to alleviate convergence to local minima, Nonlinear Analysis: Theory, Methods and
Applications, vol. 47, 3419-3424, 2001.
55. Plagianakos V.P. ,
Magoulas G.D. and Vrahatis M.N. , Learning in multilayer perceptrons
using global optimization strategies, Nonlinear Analysis:
Theory, Methods and Applications, vol. 47, 3431-3436, 2001.
56. Karkanis S., Magoulas G.D. and
Theofanous N., Image Recognition and Neuronal
Networks: Intelligent Systems for the Improvement of Imaging Information,
Minimally Invasive Therapy and Allied Technologies, vol. 9(3-4), 225-230,
August 2000.
57. Magoulas G.D. and Vrahatis M.N., A Class of Adaptive
Learning Rate Algorithms Derived by One-Dimensional Subminimization Methods,
Neural, Parallel and Scientific Computations, vol. 8, 147-168, 2000.
58. Pouloudi A. and Magoulas G.D. , Neural Expert Systems
in Medical Image Interpretation: Development, Use and Ethical Issues,
Journal of Intelligent Systems, vol.10 (5-6), 451-471, 2000.
59. Vrahatis M.N., Androulakis G.S.,
Lambrinos J.N. and Magoulas G.D., A class of gradient unconstrained
minimisation algorithms with adaptive stepsize, Journal of
Computational and Applied Mathematics, vol. 114, 367-386, 2000.
60. Vrahatis M.N., Magoulas G.D. and
Plagianakos V.P., Globally convergent modification of
the Qprop method, Neural Processing Letters, vol. 12(2),
159-170, October 2000.
61. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., Improving the convergence of the
back-propagation algorithm using learning rate adaptation methods,
Neural Computation, vol. 11, 1769-1796, 1999.
62. Androulakis G.S., Magoulas G.D. and
Vrahatis M.N., Geometry of learning: visualizing the
performance of neural network supervised training methods,
Nonlinear Analysis: Theory, Methods and Applications, vol. 30, 4539-4544, 1997.
63. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., Effective back-propagation training
with variable stepsize, Neural Networks, vol.10, 69-82, 1997.
64. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., On the alleviation of
the problem of local minima in back-propagation, Nonlinear
Analysis: Theory, Methods and Applications, vol. 30, 4545-4550, 1997.
65. Vrahatis M.N., Androulakis G.S. and
Magoulas G.D., On the acceleration
of the back-propagation training algorithm, Nonlinear
Analysis: Theory, Methods and Applications, vol. 30, 4551-4554, 1997.
66. King R.E., Magoulas G.D. and
Stathaki A.A., Multivariable fuzzy controller design, Control Engineering
Practice, vol.2, 431-437, 1993.
67. Magoulas G.D., King R.E. and
Stathaki A.A., Design of industrial multivariable fuzzy controllers, Studies in
Informatics and Control, vol.2, 253-261, 1993.
Home - Teaching - Publications - Bio - Blog - Department
C. Articles in books and edited
volumes
1. Sikora T.D., Magoulas G. D., Finding
Relevant Dimensions in Application Service Management Control. Liming Chen,
Supriya Kapoor, Rahul Bhatia (Eds.), Intelligent Systems for Science and
Information, Extended and Selected Results from the Science and Information
Conference, Studies in Computational Intelligence, vol. 542, pp 335-353, 2014.
2. Charlton P. & Magoulas G.D.
Context-aware Framework for Supporting Personalisation and Adaptation in
Creation of Learning Designs. S. Graf, F. Lin, Kinshuk & R. McGreal (Eds.)
Intelligent and Adaptive Learning Systems: Technology Enhanced Support for
Learners and Teachers. Hershey, PA: IGI Global, 2011.
3. Peng C-C and Magoulas G.D.,
Nonmonotone Learning of Recurrent Neural Networks in Symbolic Sequence
Processing Applications, Palmer-Brown, D., Draganova, Ch., Pimenidis, E.,
Mouratidis, H. (Eds.), Engineering Applications of Neural Networks,
Communications in Computer and Information Science Series, Springer Berlin
Heidelberg, vol. 43, pp. 325-335, 2009, ISBN: 978-3-642-03969-0.
4. Charlton, P. and Magoulas, G. D. Next
Generation Environments for Context-Aware Learning Design, Hatzilygeroudis, I.
and Prentzas, J. (eds.), Combinations of Intelligent Methods and Applications,
vol. 8, Smart Innovation, Systems and Technologies Series, Springer Berlin
Heidelberg, pp. 125-143, 2011, ISBN: 978-3-642-19618-8.
5. Van Labeke N., Magoulas G.D. and
Poulovassilis A., Searching for “People Like Me” in a Lifelong Learning System,
Learning in the Synergy of Multiple Disciplines, Proceedings of the 4th
European Conference on Technology Enhanced Learning (EC-TEL 2009) Nice, France,
Sept 29–Oct 2, 2009, U. Cress, V. Dimitrova, M. Specht (Eds.), Lecture Notes in
Computer Science, Volume 5794, Springer, pp. 106-111, 2009.
6. Van Labeke N., Poulovassilis A. and
Magoulas G.D., Using Similarity
Metrics for Matching Lifelong Learners, Intelligent Tutoring
Systems, Lecture Notes in Computer Science, vol. 5091, Proceedings of the 9th
International Conference on Intelligent Tutoring Systems (ITS 2008), B.
P.Woolf, E. Aïmeur, R. Nkambou, S. Lajoie (Eds.), Springer, pp. 142-151, 2008.
7. Dimakopoulos D. and Magoulas G.D.,
An architecture for a personalised mobile environment to facilitate contextual
lifelong learning, H. Ryu and D. Parsons (eds.), Innovative Mobile Learning,
chapter 12, 2009.
8. Peng C.-C. and
Magoulas G.D., Sequence Processing with Recurrent Neural Networks, Encyclopedia
of Artificial Intelligence, forthcoming.
9. de Freitas S., Harrison I., Magoulas
G.D., Papamarkos G., Poulovassilis A., Van Labeke N., Mee A., and Oliver M., L4All: a
Web-Service Based System for Lifelong Learners, S. Salerno, M.
Gaeta, P. Ritrovato, N. Capuano, F. Orciuoli, S. Miranda and A. Pierri (eds.), The Learning Grid
Handbook: Concepts, Technologies and Applications, Volume 2: The
Future of Learning, IOS Press, 2008, ISBN: 978-1-58603-829-8.
10. Magoulas G.D., User Modeling in Information
Portals, Encyclopedia of Portal Technologies and Applications, Arthur Tatnall (ed.), vol II,
Information Science Reference, ISBN: 978-1-59140-989-2, April 2007.
11. Peng C.-C. and Magoulas G.D.,
Adaptive Self-scaling Non-monotone BFGS Training Algorithm for Recurrent Neural
Networks, Artificial Neural Networks, J. Marques de Sá et al. (eds.),
Proceedings of the 17th ICANN 2007, Part I, Lecture Notes in Computer Science
vol. 4668, pp. 259–268, 2007.
12. Plagianakos V.P., Magoulas G.D. and
Vrahatis M.N., Improved learning of neural nets through global search, Global Optimization
- Scientific and Engineering Case Studies, János D. Pintér
(ed.), Series: Nonconvex Optimization and Its Applications, Vol. 85,
Springer-Verlag New York Inc, pp. 361- 388, 2006 (ISBN: 0-387-30408-8).
13. Magoulas G.D, Web-based instructional
systems, Encyclopedia of
Human Computer Interaction, Claude Ghaoui (ed.), IDEA publishing, ISBN: 1-59140-562-9, pp. 729-738, 2005.
14. Magoulas G.D. and Vrahatis M.N., Parameter
optimization algorithm with improved convergence properties for adaptive
learning, In the Frontiers of Computational Science, Lecture
Series on Computer and Computational Sciences, Vol. 3, G. Maroulis and Th.
Simos (eds.), Brill Academic Publishers, Leiden, The Netherlands, pp.384-398,
2005 (ISBN 90-6764-442-0).
15. Vrahatis M.N. and Magoulas G.D.,
Computational Approaches to Artificial Intelligence: Theory, Methods,
Applications. Lecture Series on Computer and Computational Sciences, Advances
in Computational Methods in Sciences and Engineering 2005, Selected papers from
the International Conference of Computational Methods in Sciences and
Engineering (ICCMSE 2005), Th. Simos, G. Maroulis, (eds.), Volume 4B, 2005,
pp.1413-1415, VSP/Brill Academic Publishers, The Netherlands, (ISBN:
9067644447).
16. Vrahatis, M.N. and Magoulas G.D,
Advances in Computational Intelligence: Theory, Methods, Applications. Selected
papers from the International Conference of Numerical Analysis and Applied
Mathematics (ICNAAM), Lecture Series on Computer and Computational Sciences, T.
Simos, G. Psihoyios, G. Tsitouras (eds), Wiley-Vch, 869-871, 2005 (ISBN:
3-527-40652-2).
17. Dounias G., Magoulas G. and Linkens
D., Intelligent Technologies in Bioinformatics and Medicine: An Introduction to
the Present Edition, in G. Dounias, G. Magoulas and D. Linkens (eds.),
Intelligent Technologies in Bioinformatics and Medicine, Published by the Univ.
of the Aegean and EUNITE (2004), pp. 1-4.
18. Frias-Martinez E., Magoulas G.D.,
Chen S., and Macredie R. Recent Soft Computing Approaches to User Modeling in
Adaptive Hypermedia. Lecture Notes in Computer Science, vol. 3137, Adaptive
Hypermedia and adaptive web-based systems, Proceedings of 3rd Int Conf Adaptive
Hypermedia, Paul De Bra, Wolfgang Nejdl (eds),
Springer, pp. 104-113, 2004.
19. Magoulas, G. D., Chen, S. Y., and
Dimakopoulos, D. A Personalised Interface for Web Directories based on
Cognitive Styles. Lecture Notes in Computer Science, vol. 3196, User-Centered
Interaction Paradigms for Universal Access in the Information Society: Revised
Selected Papers of the 8th ERCIM Workshop on User Interfaces for All,
Springer-Verlag, pp. 159-166, 2004, ISBN: 3-540-23375-X.
20. Stathacopoulou R., Grigoriadou M.,
Samarakou M., Magoulas G.D., Using Simulated Students for Machine Learning.
Lecture Notes in Computer Science, vol. 3220, Proceedings of the 7th
International Conference on Intelligent Tutoring Systems (ITS 2004), James C.
Lester, Rosa Maria Vicari, Fabio Paraguau, Springer, pp. 889-891, 2004.
21. Anastasiadis A.D., Magoulas G.D.,
and Liu X. Classification of Protein Localisation Patterns via Supervised
Neural Network Learning. Lecture Notes in Computer Science, vol. 2810, Advances
in Intelligent Data Analysis V, Proceedings of the 5th International Symposium
on Intelligent Data Analysis, M. Berthold, H.-J. Lenz, E. Bradley et al.
(eds.), Berlin: Springer-Verlag, pp. 430-439, 2003.
22. O’Neill P., Magoulas G. D., and Liu
X. Obtaining Quality Microarray Data via Image Reconstruction. Lecture Notes in
Computer Science, vol. 2810, Advances in Intelligent Data Analysis V,
Proceedings of the 5th International Symposium on Intelligent Data Analysis, M.
Berthold, H.-J. Lenz, E. Bradley et al. (eds.), Berlin: Springer-Verlag, pp.
364-375, 2003.
23. Grigoriadou, M., Kornilakis, H.,
Papanikolaou, K.A., and Magoulas, G.D. Fuzzy Inference for Student Diagnosis in
Adaptive Educational Systems. Lecture Notes in Artificial Intelligence, vol.
2308, Methods and Applications of Artificial Intelligence: Proceedings of the
2nd Hellenic Conference on AI, SETN2002, Vlahavas and C.D. Spyropoulos (eds.),
Berlin: Springer-Verlag, pp. 191-202, 2002.
24.
Papanikolaou
K.A., Grigoriadou M., Kornilakis H., and Magoulas G.D. INSPIRE: an INtelligent
System for Personalized Instruction in a Remote Environment. Lecture Notes in
Computer Science, vol. 2266, Hypermedia: Openess, Structural Awareness, and
Adaptivity, S. Reich. M.
Tzagarakis, P.M.E. De Bra, Berlin, Heidelberg: Springer-Verlag, pp. 215-225,
2002.
25. Ghinea G. and Magoulas G. D.,
Perceptual considerations for quality of service management: an integrated
architecture. Lecture Notes in Computer Science, Proceedings of the User
Modeling Conference, Springer, 234-236, 2001.
26. Magoulas G.D. and Prentza A., Machine learning in
medical applications, in Machine Learning and its
Applications: Advanced Lectures, G. Paliouras, V. Karkaletsis and C.D.
Spyropoulos (Eds.), Lecture Notes in Artificial Intelligence, vol. 2049,
Springer-Verlag, pp. 300-307, 2001.
27. Parsopoulos, K., Plagianakos, V.P.,
Magoulas, G.D., and Vrahatis M.N., Improving the particle swarm
optimizer by function “stretching”, in Advances in convex
analysis and global optimization, Hadjisavvas N. and Pardalos P. (ed.), vol.
54, Noncovex Optimization and its Applications, Kluwer Academic Publishers,
Dordrecht, The Netherlands, 2001, Chapter 28, pp.445-457, ISBN 0-7923-6942-4.
28. Plagianakos V.P., Magoulas G.D. and
Vrahatis M.N., Supervised training using global
search methods, in Advances in convex analysis and global
optimization, Hadjisavvas N. and Pardalos P. (ed.), vol. 54, Noncovex
Optimization and its Applications, Kluwer Academic Publishers, Dordrecht, The
Netherlands, 2001, Chapter 26, pp.421-432, ISBN 0-7923-6942-4.
29. Plagianakos V.P., Magoulas G.D. and
Vrahatis M.N., Learning rate adaptation in
stochastic gradient descent, in Advances in convex analysis
and global optimization, vol. 54, Noncovex Optimization and its Applications,
Hadjisavvas N. and Pardalos P. (ed.), Kluwer Academic Publishers, Dordrecht,
The Netherlands, 2001, Chapter 27, pp.433-444, ISBN 0-7923-6942-4.
30. Papanikolaou K., Magoulas G.D., and
Grigoriadou M., A connectionist approach for supporting personalized learning
in a web-based learning environment. Lecture Notes in Computer Science, vol.
1892, Proceedings of the International Conference on Adaptive Hypermedia and
Adaptive Web-based Systems, Springer, pp. 189-201, 2000.
31. Magoulas G.D., Plagianakos V.P.,
Androulakis G.S. and Vrahatis M.N., A framework for the development of globally
convergent adaptive learning rate algorithms. Advances in Intelligent Systems
and Computer Science, N.E. Mastorakis ed., World Scientific and Engineering
Society Press, pp.207-212, 1999.
32. Magoulas G.D., Plagianakos V.P.,
Androulakis G.S. and Vrahatis M.N., A framework for the development of globally
convergent adaptive learning rate algorithms, in Advances in Intelligent
Systems and Computer Science, N.E. Mastorakis ed., World Scientific and
Engineering Society Press, 1999, pp.207-212.
33. Plagianakos V.P., Magoulas G.D.,
Androulakis G.S. and Vrahatis M.N., Global search methods for neural network
training. Advances in Intelligent Systems and Computer Science, N.E. Mastorakis
ed., World Scientific and Engineering Society Press, pp.47-52, 1999.
34. Magoulas G.D. and Vrahatis M.N., A
model for local convergence analysis of batch-type training algorithms with
adaptive learning rates, in Recent Advances in Circuits and Systems,
Mastorakis, N. E. (ed.), World Scientific, pp. 321-326, 1998.
35. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., A training method for discrete multilayer neural
networks, in Mathematics of Neural Networks: Models, Algorithms &
Applications, Ellacot, S. W., Mason J. C. and I. J. Anderson (eds.), Kluwer
Academic Publishers, Operations Research/Computer Science Interfaces series,
chapter 41, pp. 245-249, 1997.
36. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., Neural network supervised training based on a
dimension reducing method, in Mathematics of Neural Networks: Models,
Algorithms & Applications, Ellacot, S. W., Mason, J. C. and Anderson, I. J.
(eds.), Kluwer Academic Publishers, Operations Research/Computer Science
Interfaces series, chapter 42, pp. 250-254, 1997.
37. Androulakis G.S., Magoulas G.D. and
Vrahatis M.N., Minimization techniques in neural network supervised training,
In Selected Works of the 6th International Colloquium on Differential
Equations, VSP International Science Publishers, pp. 9-16, 1996.
Home - Teaching - Publications - Bio - Blog - Department
D. Conference and workshop papers
1.
Mosca
A., and Magoulas G.D. Adapting Resilient Propagation for Deep Learning,
Proceedings of the 15th UK Workshop on Computational Intelligence, University
of Exeter, 7-9 September 2015, http://arxiv.org/pdf/1509.04612.pdf.
2.
Stamate
C. , Magoulas G.D., Thomas M.S.C. Transfer learning approach for
financial applications, Proceedings of the 15th UK Workshop on
Computational Intelligence, University of Exeter, 7-9 September 2015, http://arxiv.org/pdf/1509.02807.pdf.
3.
Adam
S., Karras D., Magoulas G.D. and Vrahatis M., Reliable estimation
of a neural network's domain of validity through interval analysis based
inversion, Proceedings of the International Joint Conference
Neural Networks, 12-17 July 2015, Killarney, IEEE, Official URL:
http://dx.doi.org/10.1109/IJCNN.2015.7280794
4.
Maitrei
K.i, Magoulas G.D., Thomas M.S.C., Transfer learning
across heterogeneous tasks using behavioural genetic principles,
Proceedings of the 13th UK Workshop on Computational Intelligence, pp.151-158,
2013.
5.
Sikora,
T.D.; Magoulas, G.D., Finding relevant dimensions in Application Service
Management control: A features selection approach, IEEE Science and Information
Conference (SAI), 2013, pp.387-395, 7-9 Oct. 2013.
6.
Sikora
T. and Magoulas G.D., Neural Adaptive Control in Application Service Management
Environment, In Proc. of the 13th International Conference on Engineering
Applications of Neural Networks, 20-23 September 2012, London, C. Jayne, S.
Yue, and L. Iliadis (eds.), Springer CCIS 311, pp. 223–233, 2012.
7.
Adam
S.P., Magoulas G.D., and Vrahatis M.N., Direct Zero-Norm Minimization for
Neural Network Pruning and Training, In Proc. of the 13th International
Conference on Engineering Applications of Neural Networks, 20-23 September
2012, London, C. Jayne, S. Yue, and L. Iliadis (eds.), Springer CCIS 311, pp.
295–304, 2012.
8.
Kohli
M., Magoulas G.D., and Thomas M., Hybrid Computational Model for Producing
English Past Tense Verbs, In Proc of the 13th International Conference on
Engineering Applications of Neural Networks (EANN), 20-23 September 2012,
London, C. Jayne, S. Yue, and L. Iliadis (eds.), Springer CCIS 311, pp.
315–324, 2012.
9.
Cocea
M. and Magoulas G.D., Learning Task-related Strategies from User Data through
Clustering, In Proc of 12th IEEE International Conference on Advanced Learning
Technologies, 400-404, 2012.
10. Cocea M. and Magoulas G.D.,
Context-dependent Feedback Prioritisation in Exploratory Learning Revisited, In
Proc UMAP 2011, Girona, Spain.
11. Charlton P., Magoulas G.D., Autonomic Computing and Ontologies to Enable
Context-aware Learning Design, Proc. 22nd International
Conference on Tools with Artificial Intelligence, 27-29 Oct. 2010, Arras,
France, pp. 286-291.
12. Lewis T.E., Magoulas G.D., Tweaking
a Tower of Blocks Leads to a TMBL: Pursuing Long Term Fitness Growth in Program
Evolution, Proc. IEEE Conference Evolutionary Computation, WCCI
2010 IEEE World Congress on Computational Intelligence July, 18-23, 2010 -
CCIB, Barcelona, Spain, pp. 4465-4472.
13. Voulgaris Z, Magoulas G.D., Discernibility-based
Algorithms for Classification. In Proc. Conf. Numerical Analysis (NumAn2010),
Chania, Crete, Greece, pp. 266-272 (ISBN 978-960-8475-14-4).
14. Cocea M., Gutierrez-Santos S.,
Magoulas G.D., Adaptive Modelling of Users’ Strategies in Exploratory Learning
Using Case-Based Reasoning. In Proc. 14th International Conference on
Knowledge-Based and Intelligent Information & Engineering Systems (KES
2010), 8-10 September 2010 Cardiff, Wales, UK, Rossitza Setchi, Ivan Jordanov,
Robert J. Howlett and Lakhmi C. Jain (eds), Lecture Notes in Computer Science,
vol. 6277, pp. 124-134.
15. Cocea M., Magoulas G.D., Group
Formation for Collaboration in Exploratory Learning Using Group Technology
Techniques, In Proc. 14th International Conference on Knowledge-Based and
Intelligent Information & Engineering Systems (KES 2010), 8-10 September
2010 Cardiff, Wales, UK, Rossitza Setchi, Ivan Jordanov, Robert J. Howlett and
Lakhmi C. Jain (eds), Lecture Notes in Computer Science, vol. 6277, pp.
103-113.
16. Gutiérrez Santos S., Mavrikis M.,
Magoulas G.D., Layered Development and Evaluation for Intelligent Support in
Exploratory Environments: The Case of Microworlds. In Proc of the Intelligent
Tutoring Systems Conference, vol. 1, 2010, pp. 105-114.
17. Charlton P., Magoulas G.D., Self-configurable
framework for enabling context-aware learning design. In Proc.
IEEE Conf. of Intelligent Systems, 2010, pp. 1-6.
18. Gutiérrez Santos S., Mavrikis M.,
Magoulas G.D., Sequence Detection for Adaptive Feedback Generation in an
Exploratory Environment for Mathematical Generalisation. In Proc. 14th
International Conference on Artificial Intelligence: Methodology, Systems, and
Applications (AIMSA 2010), Varna, Bulgaria, September 8-10. 2010, Darina
Dicheva and Danail Dochev (eds), Lecture Notes in Computer Science, vol. 6304,
2010,pp 181-190.
19. Gutiérrez Santos S., Cocea M.,
Magoulas G.D., A Case-Based Reasoning Approach to Provide Adaptive Feedback in
Microworlds. In Proc. Intelligent Tutoring Systems Conference, vol. 2, 2010,
pp. 330-333.
20. Cocea M., Magoulas G.D., Identifying
user strategies in exploratory learning with evolving task modelling. In Proc.
IEEE Conf. of Intelligent Systems, 2010, pp. 13-18.
21. Cocea, M, Gutierrez-Santos, S. Magoulas,
G.D. Enhancing Modelling of Users’ Strategies in
Exploratory Learning through Case-base Maintenance. In
Proceedings of 14th UK Workshop on Case-Based Reasoning, 2009, pp. 2-13.
22. Lewis T.E., Magoulas G.D. Strategies
to Minimise the Total Run Time of Cyclic Graph Based Genetic Programming with
GPUs, The ACM Genetic and Evolutionary Computation Conference
(GECCO-2009), pp. 1379-1386.
23. Cocea M., Magoulas G., Context-dependent
Personalised Feedback Prioritisation in Exploratory Learning for Mathematical
Generalisation. Proceedings of the 17th International Conference
User Modelling, Adaptation and Personalisation Conference, UMAP 2009 (formerly
UM and AH), pp. 271-282.
24. Cocea, M., Magoulas, G. Identifying
strategies in users exploratory learning behaviour for mathematical
generalisation. In Proc. 14th International Conference on
Artificial Intelligence in Education (AIED 2009), Building Learning Systems
that Care: From Knowledge Representation to Affective Modelling, vol. 200
Frontiers in Artificial Intelligence and Applications, V. Dimitrova, R.
Mizoguchi, B. Du Boulay and A. Graesser (eds.), July 2009, pp 626-628.
25. Cocea, M., Magoulas, G. Task-oriented modeling of learner behaviour in
exploratory learning for mathematical generalisation. In
Proceedings of the 2nd
International Workshop on Intelligent Support for Exploratory
Environments (ISEE’09), in conjunction with the 14th International Conference
on Artificial Intelligence in Education (AIED 2009), pp. 16-24.
26. de Freitas, S. Rebolledo-Mendez, G.,
Liarokapis, F., Magoulas, G., Poulovassilis, A. Developing
an evaluation methodology for immersive learning experiences in a virtual world.
In Rebolledo-Mendez, G., Liarokapis, F., de Freitas, S. (Eds) Proceedings of
2009 Conference in Games and Virtual Worlds for Serious Applications, IEEE, pp
43-50.
27. Cocea M., Gutierrez-Santos S. and
Magoulas G., Challenges for Intelligent Support in Exploratory Learning: the
case of ShapeBuilder. In Proceedings of the
1st International Workshop on Intelligent Support for Exploratory Environments
(ISEE08), in conjunction with the third European Conference on
Technology-Enhanced Learning (EC-TEL ’08).
28. Cocea M. and Magoulas G., Combining
intelligent methods for learner modelling in exploratory learning environments,
in Proceedings of the 1st International Workshop on Combinations of Intelligent
Methods and Applications (CIMA 2008), in conjunction with the 18th European
Conference on Artificial Intelligence (ECAI-08), pp. 13–18.
29. Lewis T. E and Magoulas G.D., TREAD: A New
Genetic Programming Representation Aimed at Research of Long Term Complexity
Growth, The ACM Genetic and Evolutionary Computation Conference
(GECCO’08), July 12–16, 2008, Atlanta, Georgia, USA, pp. 1339-1340.
30. Voulgaris Z. and Magoulas G. D., A discernibility-based approach to feature selection
for microarray data, Proceedings of IEEE International
Conference of Intelligent Systems, Varna, Bulgaria, Sept. 2008, vol.3, pp. 21.2-21.7.
31. Voulgaris Z. and Magoulas G. D., Dimensionality reduction for feature and pattern selection
in classification problems. Proceeding of The Third
International Multi-Conference on Computing in the Global Information
Technology, Athens, Greece, July 2008, pp. 160-165.
32. Voulgaris Z. and Magoulas G.D., Extensions of the k
Nearest Neighbour Methods for Classification Problems, Proc. of
the 26th IASTED International Conference on Artificial Intelligence
and Applications, AIA 2008, Innsbruck, Austria, February 11 – 13, 2008, pp.
23-28.
33. Anastasiadis A.D., Georgoulas G.,
Magoulas G.D., and Tzes A., Adaptive Particle Swarm Optimizer with Nonextensive
Schedule, Proceedings of the Genetic and Evolutionary Computation Conference
2007 (GECCO’07), July 7–11, 2007, London, UK, pp. 168.
34. Anastasiadis A.D., Magoulas, G.D.,
Georgoulas G., and Tzes A., Nonextensive Particle Swarm Optimization Methods,
Proceedings of the Conference in Numerical Analysis (NumAn2007), September 3-7,
Kalamata, pp. 15-18.
35. Baajour H., Magoulas G. D., and
Poulovassilis A., Modelling the
lifelong learner in a services-based environment, Proceedings of
the 2nd International Conference on Internet Technologies and
Applications (ITA 07), Wrexham, North East Wales, UK 4-7 September 2007, pp.
191-201.
36. Baajour H., Magoulas G. D., and
Poulovassilis A., Designing
services-enabled personalisation for planning of lifelong learning based on
individual and group characteristics, Proceedings of the
Workshop on Personalisation in E-Learning Environments at Individual and Group
Level, 11th International Conference on User Modeling (UM 2007), Corfu, Greece,
25-29 June 2007, pp. 8-15.
37. Peng C.-C., and Magoulas G.D.
Effective Modification of the BFGS Method for Training Recurrent Neural
Networks, Proceedings of the Conference in Numerical Analysis (NumAn2007),
September 3-7, Kalamata, pp. 113-117.
38. Peng C.-C. and Magoulas G.D.,
Adaptive Nonmonotone Conjugate Gradient Training Algorithm for Recurrent Neural
Networks, Proc. 19th IEEE International Conference on Tools with Artificial
Intelligence 2007 (ICTAI’07), 29-31 October 2007, Patras, Greece, pp. 374-381.
39. Dimakopoulos, D.N. and Magoulas,
G.D. A personalised
mobile environment for lifelong learners, Proceedings of
IADIS International Conference on WWW/Internet 2006, October 5-8, 2006, Murcia,
Spain, 31-38.
40. Magoulas, G.D. and Dimakopoulos, D.
An Adaptive Fuzzy Model for Personalization with Evolvable User Profiles,
Proceedings of IEEE 2nd International Symposium on Evolving Fuzzy Systems,
September 7-9, 2006, Ambelside, Lake District, UK, 336-341.
41. Magoulas G.D., Papamarkos G.,
Poulovassilis A., A Services-enabled Environment for Personalising Lifelong
Learning Pathways, Proceedings of Workshops held at the 4th
International Conference on Adaptive Hypermedia and Adaptive Web-based Systems,
Dublin, Ireland, June 20, 2006, Lecture Notes in Learning and Teaching,
Weibelzahl, S., Cristea, A., editors, Dublin: National College of Ireland,
2006. (ISSN 1649-8623), 140-147.
42. de Freitas S., Magoulas G.D., Oliver
M., Papamarkos G., Poulovassilis A., Harrison I, Mee A., L4All - a web-service
based system for Lifelong Learners, Proceedings of eChallenges'2006, Workshop
on Next Generation in Technology Enhanced Learning, October 25-27, 2006,
Barcelona, IOS Press, pp 1477-1484.
43. Magoulas G.D. and Anastasiadis A., A
nonextensive probabilistic model for global exploration of the search space. In
T. Simos, G. Psihoyios, G. Tsitouras, Proceedings of International Conference
of Numerical Analysis and Applied Mathematics (ICNAAM), 16-20 September 2005,
Rhodes, Greece, Wiley-Vch, 878-881 (ISBN: 3-527-40652-2).
44. Magoulas G.D. and Dimakopoulos D.N. Designing
Personalised Information Access to Structured Information Spaces,
Proceedings of the Workshop on New Technologies for Personalized Information
Access, 10th International conference on User Modeling, July 24-29, 2005,
Edinburgh, Scotland, UK, 64-73.
45. Magoulas, G.D. and Dimakopoulos, D.
Personalisation in e-learning: an approach based on services, Proceedings of
IADIS International Conference on WWW/Internet 2005, October 19-22, 2005,
Lisbon, Portugal, 312-316.
46. Anastasiadis A.D., and Magoulas G.D.,
Nonextensive
Entropy and Regularization for Adaptive Learning, Proc. of
the IEEE International Joint Conference on Neural Networks (IJCNN-04),
Budapest, Hungary, 25-29 July, 2004, vol. 2, 1067-1072.
47. Anastasiadis A.D., Magoulas G.D.,
and Vrahatis M.N., A New Learning
Rates Adaptation Strategy for the Resilient Propagation Algorithm.
In M. Verleysen (ed.), Proceedings of the 12th European Symposium on Neural
Networks (ESANN-04), April 28-30, Bruges, Belgium, D-side Publications: Evere,
1-6, 2004.
48. Magoulas G.D., Plagianakos V.P.,
Tasoulis D.K., and Vrahatis M.N., Tumor detection in
colonoscopy using the unsupervised k-windows clustering algorithm and neural
networks. In Proceedings of the Fourth European Symposium on
Biomedical Engineering, Session 3, June 25-27, 2004, Patras, Greece.
49. Ghinea G. and Magoulas G.
Integrating Perceptech Requirements through Intelligent Computation of
Priorities in Multimedia Streaming, Lecture Series on Computer and
Computational Sciences, Vol. 1, Proceedings of the International Conference of
Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004), VSP
International Science Publishers, Zeist, The Netherlands, 2004,pp.856-859.
50. Anastasiadis A.D., Magoulas G.D. and
Vrahatis M.N., A globally convergent Jacobi-bisection method for neural network
training, Lecture Series on Computer and Computational Sciences, Vol. 1,
Proceedings of the International Conference of Computational Methods in
Sciences and Engineering 2004 (ICCMSE 2004), VSP International Science Publishers,
Zeist, The Netherlands, 2004, pp.843-848.
51. Stathacopoulou R., Samarakou M.,
Grigoriadou M., Magoulas G.D., A Neuro-Fuzzy Approach to Detect Student's
Motivation. In Kinshuk, Chee-Kit Looi, Erkki Sutinen, Demetrios G. Sampson,
Ignacio Aedo, Lorna Uden and Esko Kahkonen, Proceedings of the IEEE
International Conference on Advanced Learning Technologies (ICALT 2004), 30
August-1 September 2004, Joensuu, Finland, 71-75, IEEE Computer Society.
52. O'Neill P., Magoulas G.D., Liu X.,
Quality Processing of Microarray Image Data through Image Inpainting and
Texture Synthesis. In Proceedings of the 2004 IEEE International Symposium on
Biomedical Imaging: From Nano to Macro (ISBI 2004), Arlington, VA, USA, 15-18
April 2004, vol. 1, 117-120.
53. Magoulas G.D., Building diverse
neural ensembles for bioinformatics applications, Proceedings of the Workshop
on Intelligent Technologies in Bioinformatics and Medicine, European Symposium
on Intelligent Technologies, Hybrid Systems and their Implementation on Smart
Adaptive Systems (EUNITE 2004), Aachen, Germany, June 10-12, 2004.
54. Chen, S. Y. and Magoulas, G. D. The
Relationships between Cognitive Styles and Information Representation in Web
Directories. In Proceedings of the LIDA Conference 2003, Libraries in the
Digital Age, May 26-30, 2003.
55. Ghinea G., Magoulas G. D. and Frank
A.O. Intelligent Protocol Adaptation for Enhanced Medical e-Collaboration. In
Proceedings of the International FLAIRS Conference, May 12-14, 2003 St.
Augustine, Florida.
56. Ghinea G., Magoulas G. D. and Thomas
J.P., Intelligent Management of QoS requirements for Perceptual Benefit. In
Proceedings 3rd Conference on Intelligent Systems Design and Applications, pp.
437-446, Tulsa, USA, 2003.
57. Anastasiadis A. and Magoulas G.D.
Neural Network-based Prediction of Proteins Localisation Sites. In Proceedings
of European Symposium on Intelligent Technologies, Hybrid Systems and their
implementation on Smart Adaptive Systems, 10-12 July 2003, Oulu, Finland, 318 –
325.
58. Anastasiadis A.D., Magoulas G.D.,
and Vrahatis M.N., An efficient
improvement of the Rprop algorithm. In M. Gori and S. Marinai
(eds.), Artificial Neural Networks in Pattern Recognition, Proceedings of the
1st Int Association of Pattern Recognition-TC3 Workshop, Florence, Italy,
September 2003, 197-201. Firenze: Stampa Digitale.
59. Magoulas, G. D., Chen, S. Y., and Papanikolaou , K. A. Integrating Layered
and Heuristic Evaluation for Adaptive Learning Environments.
In Proceedings of the Second Workshop on Empirical Evaluation of Adaptive
Systems, 9th International Conference on User Modeling UM2003, June 22-26,
2003.
60. Plagianakos V .P .,Magoulas G .D
.and Vrahatis M .N ., On-line neural network training (in Greek), Order and
Chaos in Nonlinear Dynamical Systems Vol .8, Proc. of the 9th Panhellenic
Conference /14th Summer School on Non -linear dynamics chaos and complexity,
Patras , July 23 –August 2, 2001, T .Bountis S .Ichtiaroglou and S .Pnevmatikos
(eds.).,K . Sfakianaki Editions, Thessaloniki, pp .329 –340, 2003.[SET 960-7258-16-9 ][ISBN 960-87136-2-5 ].
61. Magoulas, G.D., Eldabi, T., and Paul
R.J., Adaptive Stochastic
Search Methods for Parameter Adaptation of Simulation Models,
in Proceedings of the IEEE International Symposium on Intelligent Systems,
Varna, Bulgaria, Sept. 10-12, 2002, vol. 2, 23-27.
62. Ghinea G., Magoulas G.D., and Frank
A.O., Intelligent
Multimedia Transmission for Back Pain Treatment, in
Proceedings of European Symposium on Intelligent Technologies, Hybrid Systems
and their Implementation on Smart Adaptive Systems (EUNITE 2002), Session
"Intelligent E-health Applications in Medicine", 19-21 September
2002, Albufeira, Portugal, 309-316.
63. Magoulas G.D., Eldabi T., and Paul
R.J., Global search strategies for simulation optimization, in E. Yücesan, C.-H.
Chen, J. L. Snowdon, and J. M. Charnes, eds., Proceedings of the Winter
Simulation Conference, December 8-11, 2002, San Diego, California, vol. 2,
1978-1985.
64. Vrahatis M .N .,Magoulas
G .D .and Plagianakos V .P ., Introduction to artificial neural networks (in
Greek), Order and Chaos in Nonlinear Dynamical Systems Vol .7, Proceedings of
the 8th Panhellenic Conference /13th Summer School on Non-linear dynamics chaos
and complexity, Patras July 17 –28, 2000, T .Bountis D .Ellinas and I
.Grispolakis (eds.), Pnevmatikos publications Athens pp .225 –247, 2002.
65. Plagianakos V .P .,Magoulas G .D
.and Vrahatis M .N .,Tumor detection in colonoscopic images using hybrid
methods for on –line neural network training, Proc. Neural Networks and Expert
Systems in Medicine and Healthcare ,(NNESMED 2001), G .M .Papadourakis (ed.),
Technological Educational Institute of Crete Heraklion 2001, pp .59 –64 [ISBN
9608531659].
66. Ghinea G. and Magoulas G. D., A
novel application of the analytic hierarchy process in “perceived” quality of
service management, in Proceedings of IASTED International Conference on
Applied Informatics, Innsbruck, Austria, February 19-22, 2001, pp. 43-47.
67. Grigoriadou M., Papanikolaou K.,
Kornilakis H., and Magoulas G., Towards new forms of communication of knowledge
in educational hypermedia systems, in Proceedings of the Computer-Aided
Learning Conference (CAL2001), April 2-4, 2001, University of Warwick,
Coventry, UK.
68. Pouloudi A., Magoulas G. D.,
Grigoriadou M., Hossain S., and Kanidis V., IT supported learning in schools:
insights from the british and greek experience, in
Proceedings of the Computer-Aided Learning Conference (CAL2001), April 2-4,
2001, University of Warwick, Coventry, UK.
69. Parsopoulos, K., Plagianakos, V.P.,
Magoulas, G.D., and Vrahatis M.N., Stretching
technique for obtaining global minimizers through particle swarm optimization, in Proceedings of the Particle
Swarm Optimization Workshop, April 6-7, 2001, Indiana, USA, pp. 22-29.
70. Stathacopoulou R., Magoulas G.D.,
Grigoriadou M., and Mitropoulos D., Neural network-based fuzzy modeling of the
diagnostic process, in Proceedings of the 10th International Conference on
Artificial Intelligence in Education (AI-ED 2001), San Antonio, Texas, May
19-23 2001, USA.
71. Grigoriadou M., Papanikolaou K.,
Kornilakis H., and Magoulas G., INSPIRE: an INtelligent System for Personalized
Instruction in a Remote Environment, in P. De Bra, P. Brusilovsky & A.
Kobsa (eds), Pre-Workshop Proceedings: Third Workshop on Adaptive Hypertext and
Hypermedia, 8th International Conference on User Modeling (UM2001), Sonthofen,
Germany, July 13, 2001, 31-40.
72. Magoulas G.D. and Ghinea G., Neural network-based
interactive multicriteria decision making in a quality of perception-oriented
management scheme, in Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington DC, 15-19 July
2001, USA, vol. 4, 2536-2541.
73. Plagianakos V.P., Magoulas
G.D., Nousis N.K., and Vrahatis M.N., Training multilayer networks with
discrete activation functions, in Proceedings of the INNS-IEEE International
Joint Conference on Neural Networks, Washington DC, 15-19 July 2001, USA, vol.
4, 2805-2810.
74. Plagianakos V.P., Magoulas
G.D., Nousis N.K., and Vrahatis M.N., PVM-based training of large neural
architectures, in Proceedings of the INNS-IEEE International Joint Conference
on Neural Networks, Washington DC, 15-19 July 2001, USA, vol. 4, 2584-2589.
75. Magoulas G.D., Plagianakos V.P., and
Vrahatis M.N., Hybrid methods using evolutionary
algorithms for on-line training, in Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington DC, 15-19 July
2001, USA, vol. 3, 2218-2223.
76. Ghinea G. and Magoulas G.D., Quality of Service
for Perceptual Considerations: An Integrated Perspective, in
Proceedings of 2001 IEEE International Conf. on Multimedia & Expo
(ICME2001), 22-25 August 2001, Tokyo, Japan, 571-574.
77. Ghinea G., Magoulas G. D. and
Siamitros C., Perceptual considerations in a QoS framework: a fuzzy logic
formulation, in Proceedings of the 4th IEEE Workshop on Multimedia Signal
Processing, October 3-5, 2001, Cannes, France,
353-358.
78. Karkanis S.A., Magoulas G.D.,
Iakovidis D.K., Karras D.A. and Maroulis D.E., Evaluation of textural feature extraction schemes for
neural network-based interpetation of regions in medical images, in Proceedings of IEEE
International Conference on Image Processing (ICIP-2001), October 7-10, 2001,
Thessaloniki, Greece, vol. 1, 281-284.
79. Magoulas G.D., Plagianakos V.P. and
Vrahatis M.N., Improved Neural
Network-based Interpretation of Colonoscopy Images Through On-line Learning and
Evolution, in Proceedings of European Symposium on
Intelligent Technologies, Hybrid Systems and their Implementation on Smart
Adaptive Systems (EUNITE 2001), 12-14 December 2001, Tenerife, Spain,
402-407. Also in Adaptive Systems and Hybrid Computational Intelligence in
Medicine G .D .Dounias and D .A .Linkens (eds.),European Network of Excellence
on Intelligent Technologies for Smart Adaptive Systems Published by the
University of the Aegean Chios Greece 2001,pp .38 –43,[ISBN 960-7475-19-4 ].
80. Papanikolaou K., Magoulas G.D., and
Grigoriadou M., The role of the educational material for personalised learning
in a web-based course, in Proceedings of the 1st Research Workshop of the
European Distance Education Network (EDEN-2000): Research and Innovation in
Open and Distance Learning, Prague, Czech Republic, 16-17 March 2000, 151-154.
81. Magoulas, G.D., Plagianakos, V.P.,
and Vrahatis, M.N., Global learning rate adaptation in on-line neural network
training, in Proceedings of the 2nd International ICSC Symposium on Neural
Computation, May 23-26, 2000, Technical University of Berlin, Germany.
82. Vrahatis, M.N., Magoulas, G.D., and
Plagianakos, V.P., Neural
network supervised training as minimization problem (in
Greek), Dymamical Systems Vol. 6, Proc. of the 7th Panhellenic Conference/12th
Summer School on Non-linear dynamics, chaos and complexity, Patras, July 14-24,
1999, Pnevmatikos publications, Athens, pp. 243-262, 2000.
83. Papanikolaou K., Magoulas G.D., and
Grigoriadou M., Computational intelligence in
adaptive educational hypermedia, in Proceedings of the INNS-IEEE International
Joint Conference on Neural Networks, 24-27 July 2000, Como, Italy, vol. 6,
629-634.
84. Magoulas, G.D., Plagianakos, V.P.,
and Vrahatis, M.N., Development and convergence analysis
of training algorithms with local learning rate adaptation, in Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, 24-27 July 2000, Como,
Italy, vol. 1, 21-26.
85. Karkanis, S.A., Magoulas, G.D.,
Iakovidis, D.K., Maroulis, D.E., and Schurr, M.O., On the importance of feature
descriptors for the characterisation of texure, in Proceedings of the World
Multi-conference on Systemics, Cybernetics and Informatics, July 23-26, 2000,
Orlando, Florida, U.S.A.
86. Karkanis, S.A., Iakovidis, D.K., Maroulis,
D.E., Magoulas, G.D., and Theofanous, N.G., Tumor recognition
in endoscopic video images using artificial neural network architectures, Proceedings of the 26th Euromicro Conference,
Workshop on Medical Informatics, 5th-7th 5-7 September, 2000, Maastricht, the
Netherlands, vol. 2, 423-429.
87. Hossain S., Pouloudi A., and
Magoulas G. D., Issues of IT adoption in schools, in Proceedings of the
Business Information Technology Conference- BIT 2000, November 1-2, 2000,
Manchester, U.K.
88. Vrahatis M .N .,Magoulas G .D
.,Parsopoulos K .E .and Plagianakos V .P ., Introduction to artificial neural
network training and applications, Proceedings of the 15th Annual Conference of
Hellenic Society for Neuroscience (Neuroscience 2000), October 27 –29, 2000,
Patras Greece.
89. Magoulas G. D. ,
Papanikolaou K. and Grigoriadou M., Adaptive lesson presentation based on
connectionist knowledge representation, in Proceedings of the International
Conference in Technology and Education, Edinbrough, March 1999.
90. Grigoriadou M., Magoulas G. D. and
Panagiotou M., A hybrid decision making model for intelligent tutoring systems,
in Proceedings of the 5th International Conference of the Decision Sciences
Institute, 195-197, Athens, Greece, July 1999.
91. Magoulas G.D. and Vrahatis M.N.,
Analysis and synthesis of a class of neural network training algorithms derived
by one-dimensional subminimization methods, in Integrating Technology and Human
Decisions: Global Bridges into the 21 ST Century, Proceedings of the5th
International Conference of the Decision Sciences Institute, D .K .Despotis and
C .Zopounidis eds ., Athens, Greece, July 1999, vol. 1, pp .512 –514. 512-514,
1999.
92. Magoulas G.D., A new sign-method in
neural network training for embedded control applications, Proceedings of the
5th International Conference of the Decision Sciences Institute, 2001-2003,
Athens, Greece, July 1999.
93. Stathacopoulou R. , Magoulas G.D.
and Grigoriadou M., Neural network-based fuzzy
modeling of the student in intelligent tutoring systems, Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington, U.S.A., 10-16
July 1999, vol. 5, 3517-3521.
94. Papanikolaou K., Magoulas G.D., and
Grigoriadou M., A connectionist approach for
adaptive lesson presentation in a distance learning course, Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington, U.S.A., 10-16
July 1999, vol. 5, 3522-3526.
95. Magoulas G. D., Plagianakos V., and
Vrahatis M. N., Sign-methods for training with
imprecise error function and gradient values, Proceedings of the INNS-IEEE International
Joint Conference on Neural Networks, Washington, U.S.A., 10-16 July 1999, vol.
3, 1768-1773.
96. Plagianakos V., Vrahatis M. N. and
Magoulas G. D., Nonmonotone methods for backpropagation training with adaptive
learning rate, Proceedings of the INNS-IEEE International Joint Conference on
Neural Networks, Washington, U.S.A., 10-16 July 1999, vol. 3, 1762-1767.
97. Vrahatis M. N., Magoulas G. D., and
Plagianakos V., Convergence analysis of the
quickprop method, in Proceedings of the INNS-IEEE International Joint Conference on
Neural Networks, Washington, U.S.A., 10-16 July 1999, vol. 2, 1209-1214.
98. Karkanis, S.A., Magoulas, G.D.,
Grigoriadou, M. and Schurr, M., Detecting
abnormalities in colonoscopic images by textural description and neural
networks, in
Proceedings of the Workshop "Machine Learning in Medical Applications",
59-62, Chania, Greece, July 1999.
99. Plagianakos V., Magoulas G. D. and
Vrahatis M. N., Nonmonotone learning rules for
backpropagation networks, Proceedings of the 6th IEEE International Conference on Electronics,
Circuits and Systems, vol. 1, 291-294, Paphos, Cyprus, 5-8 September 1999.
100. Magoulas G. D., Plagianakos V., and
Vrahatis M. N., Effective neural network training
with a different learning rate for each weight, Proceedings of the 6th IEEE
International Conference on Electronics, Circuits and Systems, Paphos, Cyprus,
5-8 September 1999, vol. 1, 591-594, 1999.
101. Karkanis, S., Magoulas, G.D., Karras,
D. and Grigoriadou, M., Neural network-based textural labeling of images in
multimedia applications, in Proceedings of the 25th Euromicro Conference, 8-10
September 1999, Milan, Italy, vol. 2, 392-396.
102. Plagianakos, V.P., Magoulas, G.D.,
Androulakis, G.S., and Vrahatis, M.N., Global search methods for neural
network training, in Proceedings of the 3rd IEEE-IMACS World Multiconference on
Circuits, Systems, Communications and Computers, vol. 1, 3651-3656, Athens,
Greece, July 1999. Also in Advances in Intelligent Systems and Computer Science
N.E. Mastorakis ed .,World Scientific and Engineering
Society Press, pp .47 –52, 1999.
103. Magoulas, G.D., Plagianakos, V.P.,
Androulakis, G.S., and Vrahatis, M.N., A framework for the development of
globally convergent batch training algorithms, in Proceedings of the 3rd
IEEE-IMACS World Multiconference on Circuits, Systems, Communications and
Computers, vol. 1, 3641-3646, Athens, Greece, July 1999. Also in Advances in
Intelligent Systems and Computer Science N .E .Mastorakis ed., World Scientific
and Engineering Society Press, pp .207 –212, 1999.
104. Magoulas, G.D., Karkanis, S.,
Karras, D. and Vrahatis, M.N., Comparison study of textural
descriptors for training neural network classifiers, in Proceedings of the 3rd
IEEE-IMACS World Multiconference on Circuits, Systems, Communications and
Computers, vol. 1, 6221-6226, Athens, Greece, July 1999. Also in Computers and
Computational Engineering in Control N .E .Mastorakis (ed.),World Scientific
and Engineering Society Press 1999,pp. 193 –198.
105. Magoulas G. D., Papanikolaou K. and
Grigoriadou M., Towards a computationally
intelligent lesson adaptation for a distance learning course, in Proceedings of the 11th IEEE
International Conference on Tools with Artificial Intelligence, Chicago, 9-11 November
1999, pp. 5-11.
106. Magoulas G. D. and Pouloudi A.,
Ethical issues in the use of neural network-based methodologies for image
interpretation in medicine, in Proceedings of ETHICOMP99 - The 5th
International Conference on the Social and Ethical Impacts of Information and
Communication Technologies, LUISS Guido Carli University, Rome, Italy, October
1999.
107. Plagianakos, V.P., Magoulas, G.D.,
and Vrahatis, M.N., Optimization strategies and backpropagation
neural networks, in Proceedings of the 7th Hellenic Conference on Informatics, D.I.
Fotiadis and S.D. Nikolopoulos (eds.), Ioannina Greece August 26 –29, 1999, pp
.V .88 –V .95.
108. Magoulas G.D. and Vrahatis M.N., A
model for local convergence analysis of batch-type training algorithms with
adaptive learning rates, In Proceedings of the 2nd IMACS International
Conference on Circuits Systems & Computers, vol. 1, 86-91, Athens, Greece,
1998. Also In Recent Advances in Circuits and Systems N .E. Mastorakis ed.,
World Scientific Publishing Co .Pte .Ltd, 1998, pp .321 –326.
109. Magoulas G.D. and Vrahatis M.N., New
optimization algorithms for efficient neural network training, in Lipitakis
E.A. (ed.) Proceedings of the 4th Hellenic-European Research Conference on
Computational Mathematics and Applications, Athens, Greece, Sept. 24-26, p.
209-216, 1998 [ISBN 960-85176-7-2].
110. Papaspyridis A., Janetis J. Berger
R. and Magoulas G. D., Designing mixed fuzzy logic and PID embedded automotive
control systems with FLDE Autostudio&trade, in Proceedings of the 6th
European Congress on Intelligent Techniques and Soft Computing-EUFIT'98, 1998.
111. Androulakis G.S., Magoulas G.D. and
Vrahatis M.N., Minimization techniques in neural network supervised training,
In Proceedings of the 6th International Colloquium on Differential Equations,
Bulgaria, 1996.
112. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., A new method in neural network supervised
training with imprecision, In Proceedings of the 3rd IEEE
International Conference on Electronics Circuits & Systems, vol. 1,
287-290, 13-16 October, Rodos, Greece, 1996.
113. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., Neural network supervised training based on a
dimension reducing method, in Proceedings of the 1st International Conference
on Mathematics of Neural Networks and Applications, Lady Margaret Hall, Oxford,
England, 1995.
114. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., A training method for discrete multilayer neural
networks, in Proceedings of the 1st International Conference on Mathematics of
Neural Networks and Applications, Lady Margaret Hall, Oxford, England, 1995.
115. Michos S.E., Magoulas G.D. and Fakotakis
N., A hybrid knowledge representation model in a natural language interface to
MS-DOS, In Proceedings of the 7th IEEE International Conference on Tools with
Artificial Intelligence, 480-483, 5-8 November, Washington, U.S.A., 1995.
116. Michos S.E. and Magoulas G.D., A
hybrid approach to knowledge representation and learning in a natural language
interface to operating systems, in Proceedings of the 5th Hellenic Conference
on Informatics, 431-440, Athens, Greece, 1995.
117. King R.E. and Magoulas G.D., Adaptive
digital laguerre filters, In Proceedings of the International Conference on
Digital Signal Processing, vol.1, 46-53, 1993.
Home - Teaching - Publications - Bio - Blog - Department
E. Articles that cite my work (this list is under construction;
citations are also on Scholar and on ResearchGate, albeit these lists are
incomplete)
In
journals
-
Sotiropoulos
D.G., Stavropoulos E.C. and Vrahatis M.N., A new hybrid genetic algorithm for
global optimization, Nonlinear Analysis, Theory, Methods & Applications, 30
(7), 4529-4538, 1997.
-
Thangavadivelu
S., Colvin T.S., Fuzzy-logic-based decision support system for scheduling
tillage operations, Engineering Applications of Artificial Intelligence, 10(5),
463-472, 1997.
-
RoyChowdhury
P.,Singh Y .P .and Chansarkar R .A., Dynamic tunneling technique for efficient
training of multilayer perceptrons, IEEE Transactions on Neural Networks,
10(1), 48-55, 1999.
-
Dawson
C .W. and Wilby R .L., A comparison of artificial neural networks used for
river flow forecasting Hydrology and Earth System Sciences, 3(4), 529 –540,
1999.
-
Nakanishi
I., Itoh Y., Fukui Y. (2000). Introduction of orthonormal transform into neural filter for
accelerating convergence speed, IEICE Transactions on Fundamentals of
Electronics Communications and Computer Sciences, E83A, 2, 367-370, 2000.
-
Likothanassis
S.D., Georgopoulos E.F., Adamopoulos A.V., Structure determination and training
of neural networks using evolution programs, Neural Parallel and Scientific
Computations, 8, 29-48, 2000.
-
Yuqian
D .and Jiali H .,A hybrid learning algorithm for neural network based distance
protection Dianli Xitong Zidonghue /Automation of Electric Power Systems, 24(3), 22-47, 2000.
-
Yuqian
D .and Jiali H ., Radial basis function network (RBFN
)based distance protection Dianli Xitong Zi-donghue/Automation of Electric
Power Systemsm, 24(21) ,.23 –26, 2000.
-
Giles,
M.J., Anomalous scaling in homogeneous isotropic turbulence, Journal of Physics
A: Mathematical and General, 34 (21), pp. 4389-4435, 2001.
-
Tsirogiannis
G.A., Beligiannis G.N., Likothanassis S.D., Vrahatis M.N., Evolutionary
algorithms for computing zeros of nonlinear functions, Nonlinear Analysis,
Theory, Methods and Applications, 47(5), 3437-3442, 2001.
-
Manioudakis
G.D., Demiris E.N. and Likothanassis S.D., A self-organized neural network
based on the multi-model partitioning theory, Neurocomputing, 37, 1-29, 2001.
-
Dawson
C.W., Wilby R.L. (2001). Hydrological modelling using artificial neural
networks, Progress in Physical Geography, 25(1), 90-108, 2001.
-
Vrahatis
M.N., Ragos O., Androulakis G.S., Computing families of periodic orbits through
optimization methods, Nonlinear Analysis: Theory, Methods and Applications,
47(5), 3449-3454, 2001.
-
Satoh
K., Yoshikawa N., Nakano Y., Yang W.J., Whole learning algorithm of the neural
network for modeling nonlinear and dynamic behavior of RC members, Structural
Engineering and Mechanics, 12(5), 527-540, 2001.
-
Boutsinas
B. and Vrahatis M.N., Artificial nonmonotonic neural networks, Artificial
Intelligence, 132 (1), 1-38, 2001.
-
Engelbrecht
A .P .,Sensitivity analysis for selective learning by
feedforward neural networks Fundamenta Infortmaticae, 45(1), 295 –328, 2001.
-
Schwenker
F., Kestler H.A., Palm G., Three learning phases for radial-basis-function
networks Neural Networks, 14(4-5), 439-458, 2001.
-
Buhot
A., Gordon M.B., Robust learning and generalization with support vector
machines, Journal of Physics A-Mathematical and General, 34(21), 4377-4388,
2001.
-
Jiang
M.H., Zhang B., Zhu X.Y., Jinag M.Y., A fast hybrid algorithm of global
optimization for feedforward neural networks, Chinese Journal of Electronics,
10(2), 214-218, 2001.
-
Hsieh
S.J., Hsieh P.Y., Intelligent tutoring system authoring tool for manufacturing
engineering education. International Journal of Engineering Education, 17(6),
569-579, 2001.
-
Barandela,
R., Gasca, E., Alejo, R., Correccion de la Muestra para el Aprendizaje del Perceptron Multicapa, Inteligencia Artificial:
Ibero-American Journal of Artificial Intelligence, 13(2-9), 2001 [ISSN:
1137-3601].
-
Cristea,
A.I. and Okamoto, T. Object-oriented Collaborative Course Authoring Environment
supported by Concept Mapping in MyEnglish Teacher. Educational Technology &
Society 4, 2001.
-
Abbod
M. F., Linkens D. A., Mahfouf M. and Dounias G. Survey on the use of smart and
adaptive engineering systems in medicine, Artificial Intelligence in Medicine,
vol. 26(3), 179-209, 2002.
-
Istook
E .and Martinez T., Improved backpropagation learning in neural networks with
windowed momentum International Journal of Neural Systems, 12(3 –4), 303-318,
2002.
-
Nyoungui
A.N., Tonye E. and Akono A., Evaluation of speckle filtering and texture
analysis methods for land cover classification from SAR images, International
Journal of Remote Sensing, 23(9), 1895-1925, 2002.
-
Kärkkäinen
T., MLP in Layer-Wise Form with Applications to Weight Decay Neural
Computation, 14(6), 1451–1480, 2002.
-
Abdulkader
H .,Langlet F .,Roviras D .and Castanie F .,Natural gradient algorithm for
neural networks applied to non -linear high power amplifiers, International
Journal of Adaptive Control and Signal Processing, 16(8), 557 –576, 2002.
-
Andreou,
A.S., Parsopoulos, K.E., Vrahatis, M.N., Zombanakis, G.A., Optimal versus
required defence expenditure: The case of the Greek-Turkish arms race, Defence
and Peace Economics, 13 (4), pp. 329-347, 2002.
-
Kestler
H.A., Muller A., Hombach V. , Wohrle J., Grebe O., Palm G., Hoher M. and
Schwenker F., Decision fusion of micro -variability and signal averaged ECG
parameters from the QRS complex with RBF networks, Computers in Cardiology, 29,
297 –300, 2002.
-
Chand
S., Om H., Buffer evaluation in variable bandwidth channelization for videos,
IEEE Transactions on Consumer Electronics, 49(2), 354-358, May 2003.
-
Ηο
L .S. and Rajapakse J. C., Splice site detection with a higher-order Markov
model implemented on a neural network, Genome Informatics, 14, 64 –72, 2003.
-
Gallagher
M. and Downs T., Visualization of learning in multi–layer perceptron networks
using PCA, IEEE Transactions on Systems, Man and Cybernetics, Part B:
Cybernetics, 33(1), 28–34, 2003.
-
Daqi
G. and Genxing Y., Influences of variable scales and activation functions on
the performances of multilayer feedforward neural networks Pattern Recognition,
36(4), 869–878, 2003.
-
Karkanis,
S.A., Iakovidis, D.K., Maroulis, D.E., Karras, D.A., Tzivras, M.,
Computer-Aided Tumor Detection in Endoscopic Video Using Color Wavelet
Features, IEEE Transactions on Information Technology in Biomedicine, 7 (3),
pp. 141-152, 2003.
-
Laskari,
E.C., Parsopoulos, K.E., Vrahatis, M.N., Evolutionary operators in global
optimization with dynamic search trajectories, Numerical Algorithms, 34 (2-4),
pp. 393-403, 2003.
-
Meletiou
G.C., Tasoulis D.K, and Vrahatis M.N., Cryptography through interpolation
approximation and computational inteligence methods, Bulletin of the Greek
Mathematical Society, 48:61-75, 2003.
-
Hsiao
T.-C. R., Lin C.-W., Chiang H. K., Partial least-squares algorithm for weights
initialization of backpropagation network, Neurocomputing, 50, 237-247, 2003.
-
Ma
L., and Khorasani K., A new strategy for adaptively constructing multilayer
feedforward neural networks, Neurocomputing, 51, 361-385, 2003.
-
Maroulis,
D.E., Iakovidis, D.K., Karkanis, S.A., Karras, D.A., CoLD: A versatile
detection system for colorectal lesions in endoscopy video-frames, Computer
Methods and Programs in Biomedicine, 70 (2), pp. 151-166, 2003.
-
Ilonen
J., Kamarainen J.-K . and Lampinen J., Differential
evolution training algorithm for feed-forward neural networks, Neural
Processing Letters, 17(1), 93 –105, March 2003.
-
Jiang
M.-H., Gielen G., Zhang B. and Luo Z.-S., Fast learning algorithms for
feedforward neural networks, Applied Intelligence, 18(1), 37–54,
January-February 2003.
-
Patankar
S.J. and Jurs P.C., Classification of HIV protease inhibitors on the basis of
their antiviral potency using radial basis function neural networks, Journal of
Computer-Aided Molecular Design, 17(2-4), 155 –171, February 2003.
-
Andreou,
A.S., Parsopoulos, K.E., Vrahatis, M.N., Zombanakis, G.A., An alliance between
Cyprus and Greece: Assessing its partners' relative security contribution,
Defence and Peace Economics, 15 (5), pp. 481-495, 2004.
-
Fernandes,
A.M., Utkin, A.B., Lavrov, A.V., Vilar, R.M., Neural network based recognition
of smoke signatures from lidar signals, Neural Processing Letters, 19 (3), pp.
175-189, 2004.
-
Fraser
K., O'Neill P., Wang Z., and Liu, X., Copasetic analysis: a framework for the
blind analysis of microarray imagery, IEE Proceedings Systems Biology, 1(1),
190-196, June 2004.
-
Goltsev,
A., Secondary learning in the assembly neural network, Neurocomputing, 62 (1-4),
pp. 405-426, 2004.
-
Hatzilygeroudis,
I., Prentzas, J., Using a hybrid rule-based approach in developing an
intelligent tutoring system with knowledge acquisition and update capabilities,
Expert Systems with Applications, 26 (4), pp. 477-492, 2004.
-
Iakovidis,
D.K., Maroulis, D.E., Karkanis, S.A., Papageorgas, P., Tzivras, M., Texture
multichannel measurements for cancer precursors' identification using support
vector machines, Measurement: Journal of the International Measurement
Confederation, 36 (3-4), pp. 297-313, 2004.
-
Jiang
H.-M ., Xie K. and Wang Y.-F., Design of multi-pumped Raman fiber amplifier by
particle swarm optimization, Guangdianzi Jiguang/Journal of Optoelectronics
Laser, 15(10), 1190–1193, October 2004.
-
Kumar
D.N., Raju K.S. and Sathish T., River flow forecasting using recurrent neural
networks, Water Resources Management, 18(2), 143 –161, April 2004.
-
Lukac
R., Plataniotis K.N., Smolka B., Venetsanopoulos A.N., A multichannel
order-statistic technique for cDNA microarray image processing, IEEE
Transactions on NanoBioscience, 3(4), 272-285, Dec. 2004.
-
Ma
L. and Khorasani K., New training strategies for constructive neural networks
with application to regression problems, Neural Networks, 17(4), 589–609, 2004.
-
Müller
H., Michoux N., Bandon D., and Geissbuhler A., A review of content-based image
retrieval systems in medical applications—clinical benefits and future
directions, International Journal of Medical Informatics, vol. 73(1), 1-23,
2004.
-
Parsopoulos,
K.E., Vrahatis, M.N., On the Computation of all global minimizers through
particle swarm Optimization, IEEE Transactions on Evolutionary Computation, 8
(3), pp. 211-224, 2004.
-
Shi
Z.-J. Convergence of line search methods for unconstrained optimization,
Applied Mathematics and Computation, 157(2), 393-405, 2004.
-
Shi
Z.-J., Convergence of multi-step curve search method for unconstrained
optimization, Journal of Numerical Mathematics, 12(4), 297 –309,2004.
-
Shi
Z.-J. and Shen J., A gradient-related algorithm with
inexact line searches, Journal of Computational and Applied Mathematics,
170(2), 349–370, 2004.
-
Stefansson
Gunnar, The tutor-web: An educational system for classroom presentation,
evaluation and self-study, Computers & Education, vol. 43(4), 315-343,
2004.
-
Yang,
W., Li, Q., Survey on Particle Swarm Optimization Algorithm, Engineering
Science, 6 (5), pp. 87-94, 2004.
-
Yuan
P., Wang G.-X. and Zhang Y.-Y., Particle swarm optimization approach of solving
communication optimization problems, Dongbei Daxue Xuebao/Journal of
Northeastern University, 25(10), 934–937, 2004.
-
Zhang,
Z., Xue, R., To Solve Nonlinear Constrained Optimization Problems with Particle
Swarm Algorithm, Computer Engineering and Applications, 40 (25), pp. 90-92,
2004.
-
Zhang,
Z., Li, Y., To Solve Nonlinear Constrained Optimization Problems with Hybrid
Particle Swarm Algorithm, Computer Applications and Software, 21 (8), pp.
114-115, 2004.
-
Ribeiro
MV, Learning rate updating methods applied to adaptive fuzzy equalizers for
broadband power line communications, EURASIP Journal Applied Signal Processing,
16, 2592-2599, 2004.
-
Tar
J.K., Rudas I.J., Bitó J.F., Simulation Based Verification of the Applicability
of a Novel Branch of Computational Cybernetics in the Adaptive Control of
Imperfectly Modeled Physical Systems of Asymmetric Delay Time and Strong
Non-linearities, Acta Polytechnica Hungarica, Issue Number 1 May 2004
[http://www.bmf.hu/journal/Issue1.htm].
-
Wang
Feng-Hsu, A fuzzy neural network for item sequencing in personalized cognitive
scaffolding with adaptive formative assessment, Expert Systems with
Applications, vol. 27(1), 11-25, 2004.
-
Wu
Y. and Wang S-J., Novel quick convergence back-propagation algorithm, Tongji
Daxue Xuebao/Journal of Tongji University, 32(8), pp. 1092–1095, August 2004.
-
Zhang
X.J., Chen K.Z. and Feng X.A., Optimization of material properties needed for
material design of components made of multi-heterogeneous materials, Materials
and Design, 25(5), 369–378, 2004.
-
Bergasa-Suso
J., Sanders D.A. and Tewkesbury G.E., Intelligent browser-based systems to
assist Internet users, IEEE Transactions on Education, 48(4), 580-585, Nov.
2005.
-
Devaney
A.J., Marengo E.A. and Gruber F.K., Time-reversal-based imaging and inverse
scattering of multiply scattering point targets, J. Acoust. Soc. Am., 118 (6),
3129–3138, 2005.
-
Ghinea
G. and Thomas J.P., Quality of perception: user quality of service in
multimedia presentations, IEEE Transactions on Multimedia, 7(4), 786-789, Aug.
2005.
-
Jin,
Y.-X., Cheng, H.-Z., Wang, C.-M., Yan, J.-Y. , Zhang, L., New Parallel Particle
Swarm Optimization and its Application on Power Transmission Network Planning,
WSEAS Transactions on Circuits and Systems, 4(8), pp. 960-968, 2005.
-
Chen,
G.-C., Yu, J.-S., Particle Swarm Optimization Algorithm, Information and
Control, 34 (3), pp. 318-324, 2005.
-
Chen,
S.Y., Liu, X., Data mining from 1994 to 2004: An application-orientated review,
International Journal of Business Intelligence and Data Mining, 1 (1), pp.
4-21, 2005.
-
Chen
S. Y., Macredie R. D., The assessment of usability of electronic shopping: A
heuristic evaluation, International Journal of Information Management, vol.
25(6), 516-532, 2005.
-
Goltsev
A. and Rachkovskij D., Combination of the assembly neural network with a
perceptron for recognition of handwritten digits arranged in numeral strings,
Pattern Recognition, 38(3), 315–322, March 2005.
-
Gore
R.G., Li J., Manry M.T., Liu L.M., Yu C. and Wei J., Iterative design of neural
network classifiers through regression, International Journal on Artificial
Intelligence Tools, 14(1-2), 281–301, 2005.
-
Guzman,
E., Conejo, R., Garcia-Hervas, E., An authoring environment for adaptive
testing, Educational Technology and Society, 8 (3), pp. 66-76, 2005.
-
Jin,
Y.-X., Cheng, H.-Z., Yan, J.-Y., Zhang, L., Local best embranchment based
convergence guarantee particle swarm optimization and its use in transmission
network planning, Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese
Society of Electrical Engineering, 25 (23), pp. 12-18, 2005.
-
Karampiperis,
P., Sampson, D., Adaptive learning resources sequencing in educational
hypermedia systems, Educational Technology and Society, 8 (4), pp. 128-147,
2005.
-
Kodogiannis
V.S., Boulougoura M. and Wadge E., Improved neural network -based
interpretation of capsule endoscopic images, WSEAS Transactions on Systems,
4(9), 1499-1507, 2005.
-
Kuljis,
J., Liu, F., A comparison of learning style theories on the suitability for
eLearning, Proceedings of the IASTED International Conference on Web
Technologies, Applications, and Services, WTAS 2005, pp. 191-197, 2005.
-
Lee
Catherine Hui Min, Cheng Yuk Wing, Rai Shri, Depickere A., What affect student
cognitive style in the development of hypermedia learning system? Computers
& Education, vol. 45(1), 1-19, 2005.
-
Li,
Q., Fraley, C., Bumgarner, R.E., Yeung, K.Y., Raftery, A.E., Donuts, scratches
and blanks: Robust model-based segmentation of microarray images,
Bioinformatics, 21 (12), pp. 2875-2882, 2005.
-
Liu
H., Chen X. and Chen Y., Wavelet transform and real -time learning method for
myoelectric signal in motion discrimination, Journal of Physics: Conference
Series, 13(1), 250–253, 2005.
-
Mahfouf,
M., Nunes, C.S., Linkens, D.A., Peacock, J.E., Modelling and multivariable
control in anaesthesia using neural-fuzzy paradigms: Part II. Closed-loop
control of simultaneous administration of propofol and remifentanil, Artificial
Intelligence in Medicine, 35 (3), pp. 207-213, 2005.
-
Moshou
D., Hostens I., Papaioannou G. and Ramon H., Dynamic muscle fatigue detection
using self–organizing maps, Applied Soft Computing, 5(4), 391–398, 2005.
-
Papageorgiou
E.I. and Groumpos P.P., A new hybrid method using evolutionary algorithms to
train fuzzy cognitive maps, Applied Soft Computing, 5(4), 409–431, 2005.
-
Papageorgiou,
E.I., Parsopoulos, K.E., Stylios, C.S., Groumpos, P.P., Vrahatis, M.N., Fuzzy
cognitive maps learning using particle swarm optimization, Journal of
Intelligent Information Systems, 25 (1), pp. 95-121, 2005.
-
Pavlidis,
N.G., Parsopoulos, K.E., Vrahatis, M.N., Computing Nash equilibria through
computational intelligence methods, Journal of Computational and Applied
Mathematics, 175 (1), pp. 113-136, 2005.
-
Rajapakse
J.C. and Ηο L.S., Markov encoding for detecting signals in genomic
sequences IEEE/ACM Transactions on Computational Biology and Bioinformatics,
2(2), 131–142, 2005.
-
Schmidt
H. and Thierauf G., A combined heuristic optimization technique, Advances in
Engineering Software, 36(1), 11–19, 2005.
-
Skokos,
Ch., Parsopoulos, K.E., Patsis, P.A., Vrahatis, M.N., Particle swarm optimization:
An efficient method for tracing periodic orbits in three-dimensional galactic
potentials, Monthly Notices of the Royal Astronomical Society, 359 (1), pp.
251-260, 2005.
-
Shi
Z.-J. and Shen J., A new descent algorithm with curve
search rule, Applied Mathematics and Computation, 161(3), 753–768, 2005.
-
Shi
Z.-J. and Shen J., Convergence of descent method
without line search, Applied Mathematics and Computation, 167(1), 94–107, 2005.
-
Shi
Z.-J. and Shen J., A new super-memory gradient method with curve search rule,
Applied Mathematics and Computation, 170(1), 1 –16, 2005.
-
Wang,
J.-N., Shen, Q.-T., Shen, H.-Y., Zhou, X.-C., A Clustering-Based Niching
Particle Swarm Optimization, Information and Control, 34 (6), pp. 680-684,
2005.
-
Xiong,
Y., Lu, W.-C., Mo, Y.-B., Hu, S.-X., Particle Swarm Optimization Based on
Rotate Surface Transformation, Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of
Zhejiang University (Engineering Science), 39 (12), pp. 1946-1949+1978, 2005.
-
Wei,
J.-L., Wang, J.-H., Wu, Q.-H., Lu, N., Power System Aggregate Load Area
Modelling by Particle Swarm Optimization, International Journal of Automation
and Computing, 2 (2), pp. 171-178, 2005.
-
Wu
Y. and Wang S-J., Neural network with linear -nonlinear combined output nodes,
Tongji Daxue Xuebao/ Journal of Tongji University, 33(4), 516–519, 2005.
-
Yu
C., Manry M.T. and Li J., Effects of nonsingular preprocessing on feedforward
network training, International Journal of Pattern Recognition and Artificial
Intelligence, 19(2), 217–247, 2005.
-
Adjeroh
D.A., Zhang Y., Parthe, R., On denoising and compression of DNA microarray
images, Pattern Recognition 39 (12), pp. 2478-2493, 2006.
-
Ali
S. and Smith K.A., On learning algorithm selection for
classification, Applied Soft Computing, 6(2), 119-138, 2006.
-
Barcelos
M., Bavestrello H. and Maute K., A Schur-Newton-Krylov solver for steady-state
aeroelastic analysis and design sensitivity analysis, Computer Methods in
Applied Mechanics and Engineering, 195(17-18), 2050-2069, 2006.
-
Lin,
W., Chen, T., Analysis of two restart algorithms, Neurocomputing, 69 (16-18),
pp. 2301-2308, 2006.
-
Lloyd,
T., Bull, S., A haptic learner model, International Journal of Continuing
Engineering Education and Life-Long Learning, 16 (1-2), pp. 137-149, 2006.
-
Castellano
G., Fanelli A.M., Torsello M.A., A fuzzy clustering approach to derive profiles
from access log data, WSEAS Transactions on Information Science and
Applications 3 (12), pp. 2464-2470, 2006.
-
Chen
Nian-Shing, Kinshuk, Wei Chun-Wang and Chen Hong-Jhe, Mining e-Learning domain concept
map from academic articles, Computers & Education (2006),
doi:10.1016/j.compedu.2006.10.001
-
Chetwynd,
D., Worden, K., Manson, G., An application of interval-valued neural networks
to a regression problem, Proceedings of the Royal Society-Mathematical,
Physical and Engineering Sciences (Series A), 462(2074), 3097-3114, 2006.
-
Cui
Z., Zeng J., Sun G. Hybrid method to computing global minima combined with PSO
and BPR , Chinese Journal of Electronics, 15(4A),
949-952, October 2006.
-
Cui
Zhi-hua, and Zeng Jian-chao, Analysis and Improvement About Particle Swarm
Optimization Based on Linear Control Theory, Mini-Micro Systems, vol.27, no.5,
pp.849-853, 2006.
-
Dai
Y .H .and Yang X .Q .,A new gradient method with an optimal
stepsize property, Computational Optimization and Applications, 33(1), 73-88,
2006.
-
de Freitas, S.I., Using games and simulations for
supporting learning, Learning, Media and Technology, 31 (4), pp. 343-358, 2006.
-
Dong
Chaojun, and Qiu Zulian, Particle Swarm Optimization Algorithm Based on the
Idea of Simulated Annealing, International Journal of Computer Science and
Network Security, vol.6, no.10, pp. 152-156, 2006.
-
Dukkipati
A, Murty M.N. and Bhatnagar S., Nonextensive triangle equality and other properties
of Tsallis relative-entropy minimization, Physica A: Statistical Mechanics and
its Applications, 361 (1), pp. 124-138, 2006.
-
Flaounas,
I.N., Iakovidis, D.K., Maroulis, D.E., Cascading SVMS as a tool for medical
diagnosis using multi-class gene expression data, International Journal on
Artificial Intelligence Tools, 15 (3), pp. 335-352, 2006.
-
Gao
F, Tong H.-Q., Nonlinear least squares estimation based on improved particle
swarm optimization, Systems Engineering and Electronics, 28(5), 775-778, 2006.
-
Goel
AK, Saxena SC, Bhanot S., A fast learning algorithm for training feedforward
neural networks, International Journal of System Sciences, 37 (10), 709-722,
2006.
-
Gao
F, Tong H.-Q., Parameter estimation for chaotic system based on particle swarm
optimization, Acta Physica Sinica, 55 (2): 577-582, 2006.
-
Georgiou,
V.L., Pavlidis, N.G., Parsopoulos, K.E., Alevizos, Ph.D., Vrahatis, M.N., New
self-adaptive probabilistic neural networks in bioinformatic and medical tasks,
International Journal on Artificial Intelligence Tools, 15 (3), pp. 371-396,
2006.
-
Guang-Bin
Huang, Qin-Yu Zhu, Mao K.Z., Chee-Kheong Siew, Saratchandran P., and
Sundararajan, N., Can threshold networks be trained directly? IEEE Transactions
on Circuits and Systems II: Analog and Digital Signal Processing, 53(3),
187-191, March 2006.
-
Ho
L.S. and Rajapakse J.C., Input encoding method for identifying transcription
start sites in RNA polymerase II promoters by neural networks, Soft Computing
-A Fusion of Foundations, Methodologies and Applications, 10(4), 331–337, 2006.
-
Iakovidis
D.K., Maroulis D.E. and Karkanis S.T., An intelligent system for automatic
detection of gastrointestinal adenomas in video endoscopy, Computers in Biology
and Medicine Pages, 36(10), 1084-1103, 2006.
-
Kelly,
D., Tangney, B., Adapting to intelligence profile in an adaptive educational
system, Interacting with Computers, 18 (3), pp. 385-409, 2006.
-
Kocsis,
L., Szepesvari, C., Universal parameter optimisation in games based on SPSA,
Machine Learning, 63 (3), pp. 249-286, 2006.
-
Lappas,
G., Frank, R.J., Albrecht, A.A., A computational study on circuit size versus
circuit depth, International Journal on Artificial Intelligence Tools, 15 (2),
pp. 143-161, 2006.
-
Laskari
E.C., Meletiou G.C., Tasoulis D.K., and Vrahatis M.N., Studying the performance
of artificial neural networks on problems related to cryptography, Nonlinear
Analysis Series B: Real World Applications, 7(5), 937-942, 2006.
-
Lekakos
G., Giaglis G.M., Improving the prediction accuracy of recommendation
algorithms: Approaches anchored on human factors, Interacting
with Computers, vol. 18(3), 410-431, 2006.
-
Li
J. and Duckett T., Growing RBF networks for learning reactive behaviours in
mobile robotics, International Journal of Vehicle Autonomous Systems (IJVAS), 4
(2-4), pp. 285-307, 2006.
-
Lu
Chun-tao, Some Modified Step-size Rules and the
Convergence Properties, Journal of Guangxi Teachers Education University
(Natural Science Edition), vol.23, no.2, pp. 13-19, 2006.
-
Lukac,
R., Plataniotis, K.N., cDNA microarray image segmentation using root signals,
International Journal of Imaging Systems and Technology, 16 (2), pp. 51-64,
2006.
-
Mestre,
L., Accommodating diverse learning styles in an online environment, Reference
and User Services Quarterly, 46 (2), pp. 27-32, 2006.
-
Mangal
M., Singh M.P., Analysis of pattern classification for the multidimensional
parity-bit-checking problem with hybrid evolutionary feed-forward neural
network, Neurocomputing (2006), doi:10.1016/j.neucom.2006.02.022
-
Mourrain
B., Pavlidis N.G., Tasoulis D.K. and Vrahatis M.N., Determining the number of
real roots of polynomials through neural networks, Computers and Mathematics
with Applications, 51 (3-4), 527-536, 2006.
-
Niu
Yi-feng, and Shen Lin-cheng, Multiobjective Optimization for Multifocus Image
Fusion Using IMOPSO, Acta Electronica Sinica, vol.34, no.9, pp. 1578-1583,
2006.
-
Nykänen,
O., Inducing fuzzy models for student classification, Educational Technology
and Society, 9 (2), pp. 223-234, 2006.
-
Parrott,
D., Li, X., Locating and Tracking Multiple Dynamic Optima by a Particle Swarm
Model Using Speciation, IEEE Transactions on Evolutionary Computation, 10 (4),
pp. 440-458, 2006.
-
Pavlidis
N. G., Plagianakos V. P., Tasoulis D. K., and Vrahatis M. N., Financial
forecasting through unsupervised clustering and neural networks, Operational
Research - An International Journal, 6(2) 2006 [ISSN:1109-2858].
-
Pavlidis
N.G., Tasoulis D.K., Plagianakos V.P., and Vrahatis M.N., Computational
Intelligence Methods for Financial Time Series Modeling, International Journal
of Biffurcation and Chaos, 16(7), 2053-2062, 2006.
-
Papanikolaou,
K.A., Mabbott, A., Bull, S., Grigoriadou, M., Designing learner-controlled
educational interactions based on learning/cognitive style and learner
behaviour, Interacting with Computers, 18 (3), pp. 356-384, 2006.
-
Ribeiro
M.V., daR.Lopes R., Romano J.M.T. and Duque C.A., Impulse Noise Mitigation
Based on Computational Intelligence for Improved Bit Rate in PLC-DMT, IEEE
Transactions on Power Delivery, 21(1), 94-101, Jan. 2006.
-
Ruan
Xiao-Gang, Ding Ming-Xiao, Yu Nai-Gong and Liu Liang, Design and Simulation of
Predictive Feedback Error Learning Model, Journal of System Simulation, vol.18,
no.11, pp. 3227-3246, 2006.
-
Saidi,
H., Khelil, N., Hassouni, S., Zerarka, A., Energy Spectra of the Schrodinger
Equation and the Differential Quadrature Method: Improvement of the Solution
Using Particle Swarm Optimization, Applied Mathematics and Computation, 182
(1), 559-566, 2006.
-
Santally,
M.I., Alain, S., Personalisation in Web-based learning environments,
International Journal of Distance Education Technologies, 4 (4), pp. 15-35,
2006.
-
Siller,
M., Woods, J. Using an agent based platform to map quality of service to
experience in conventional and active networks, IEE Proceedings:
Communications, 153 (6), pp. 828-840, 2006.
-
Shi
Z.-J., Convergence of quasi-Newton method with new inexact line search, Journal
of Mathematical Analysis and Applications, 315(1), 120–131, 2006.
-
Shi
Z.-J. and Shen J., Convergence of nonmonotone line
search method, Journal of Computational and Applied Mathematics, 193(2),
397-412, 2006.
-
Shi
Z.-J. and Shen J., On memory gradient method with
trust region for unconstrained optimization, Numerical Algorithms, 41(2),
173-196, 2006.
-
Spina
R., Optimisation of injection moulded parts by using ANN-PSO approach, Journal
of Achievements in Materials and Manufacturing Engineering, vol. 15, No 1-2,
146-152, March-April 2006.
-
Song
Yu, Kou Lisong, and Ren Yongkai, Application of Low Strain Stir Measure
Technique on a Bridge Bored Pile of Guilin, Anhui Architecture, vol.13, no.4,
pp. 154-156, 2006.
-
Tasoulis
D.K., Plagianakos V.P., and Vrahatis M.N., Unsupervised clustering in mRNA
expression profiles, Computers in Biology and Medicine, 36(10), 1126-1142,
2006.
-
Tasoulis,
D.K., Spyridonos, P., Pavlidis, N.G., Plagianakos, V.P., Ravazoula, P.,
Nikiforidis, G., Vrahatis, M.N., Cell-nuclear data reduction and prognostic
model selection in bladder tumor recurrence, Artificial Intelligence in
Medicine, 38 (3), pp. 291-303, 2006.
-
Tasoulis
D.K. and Vrahatis M.N., Unsupervised clustering Using Fractal Dimension,
International Journal of Biffurcation and Chaos, 16(7), 2073-2079, 2006.
-
van den Bergh F. and Engelbrecht A .P., A study of
particle swarm optimization particle trajectories, Information Sciences,
176(8), 937-971, 2006.
-
Yannibelli,
V., Godoy, D., Amandi, A., A genetic algorithm approach to recognise students'
learning styles, Interactive Learning Environments, 14 (1), pp. 55-78, 2006.
-
Yu
Min, Sun Jun, Xu Wenbo, and Jiang Jiabao, QPSO Algorithm Based on Stretching
Technique, Computer Engineering and Applications, vol.42, no.16, 32-72, 2006.
-
Yu,
C., Manry, M.T., Li, J., Lakshmi Narasimha, P., An efficient hidden layer
training method for the multilayer perceptron, Neurocomputing, 70 (1-3), pp.
525-535, 2006.
-
Yuan,
Y-X, A New Stepsize for the Steepest Descent Method, Journal of Computational
Mathematics, 24(2), 149-156, 2006.
-
Zerarka,
A., Khelil, N., Saidi, H., A Generalised Integral Quadratic Method: Improvement
of the Solution for One Dimensional Volterra Integral Equation Using Particle
Swarm Optimisation, International Journal of Simulation and Process Modeling, 2
(1-2), pp. 85-91, 2006.
-
Zhang,
Z.-Y., Ge, S.-Y., Liu, Z.-F., Particle Swarm Optimization Algorithm and its
Application in Unit Commitment, Electric Power Automation Equipment, 26 (5),
pp. 28-31, 2006.
-
Zhang,
H., Tam, C.M., Li, H., Shi, J.J., Particle swarm optimization-supported
simulation for construction operations, Journal of Construction Engineering and
Management, 132 (12), pp. 1267-1274, 2006.
-
Argamon,
S., Whitelaw, C., Chase, P., Hota, S.R., Garg, N., Shlomo Levitan, L.,
Stylistic text classification using functional lexical features, Journal of the
American Society for Information Science and Technology, 58 (6), pp. 802-822,
2007.
-
Bennett,
T.B., Nicholson, S.W., Connecting users to numeric and spatial resources,
Social Science Computer Review, 25 (3), pp. 302-318, 2007.
-
Barcelos
M., Maute K., Aeroelastic design optimization for laminar and turbulent flows,
Comput. Methods Appl. Mech. Engrg. (2007), doi:10.1016/j.cma.2007.03.009
-
Brits
R., Engelbrecht A.P., van den Bergh F., Locating multiple optima using particle
swarm optimization, Applied Mathematics and Computation, 189, 1859–1883, 2007.
-
Castro
E.G. and Tsuzuki M.S.G., Swarm Intelligence applied in synthesis of hunting
strategies in a three-dimensional environment, Expert Systems with Applications
(2007), doi:10.1016/j.eswa.2007.02.031
-
Charvillat
V., Grigoraş R., Reinforcement learning for dynamic multimedia adaptation,
Journal of Network and Computer Applications, vol. 30(3), 1034-1058, 2007.
-
Chen
G.D., Chang C.K., Wang C.Y., Using adaptive e-news to improve undergraduate
programming courses with hybrid format, Computers & Education (2007),
doi:10.1016/j.compedu.2007.05.007
-
Dukkipati,
A., Bhatnagar, S., Murty, M.N., On measure-theoretic
aspects of nonextensive entropy functionals and corresponding maximum entropy
prescriptions, Physica A: Statistical Mechanics and its Applications, 384 (2),
pp. 758-774, 2007.
-
Erdem
R., A non-extensive statistical mechanical approach to define the equilibrium
value function in the kinetics of voltage-gated ion channels, Physica A:
Statistical and Theoretical Physics, 373, pp. 417-424, 2007.
-
Englund,
C., Verikas, A., A SOM-based data mining strategy for adaptive modelling of an
offset lithographic printing process, Engineering Applications of Artificial
Intelligence, 20 (3), pp. 391-400, 2007.
-
Frias-Martinez,
E., Chen, S.Y., Liu, X., Automatic cognitive style identification of digital library
users for
-
Personalization,
Journal of the American Society for Information Science and Technology, 58 (2),
pp. 237-251, 2007.
-
Garcia,
P., Amandi, A., Schiaffino, S., Campo, M., Evaluating Bayesian networks'
precision for detecting students' learning styles, Computers and Education, 49
(3), pp. 794-808, 2007.
-
Guzman,
E., Conejo, R., Perez-De-La-Cruz, J.-L. Adaptive testing for hierarchical
student models, User Modelling and User-Adapted Interaction, 17 (1-2), pp.
119-157, 2007.
-
Huaxiang
Zhang, Ying Fan, An adaptive policy gradient in learning Nash equilibria,
Neurocomputing, doi:10.1016/j.neucom.2007.12.007
-
Jiang
Y., Hu Tiesong, Huang ChongChao, Wu Xianing, An improved particle swarm
optimization algorithm, Applied Mathematics and Computation (2007), doi:10.1016/j.amc.2007.03.047
-
Ju,
Z., Wells, M.C., Walter, R.B., DNA microarray technology in toxicogenomics of
aquatic models: Methods and applications, Comparative Biochemistry and
Physiology - C Toxicology and Pharmacology, 145 (1), pp. 5-14, 2007.
-
Kodogiannis
V.S., Boulougoura M., Lygouras J.N. and Petrounias I., A neuro-fuzzy-based
system for detecting abnormal patterns in wireless-capsule endoscopic images , Neurocomputing, 70(4-6), pp. 704-717, 2007.
-
Kodogiannis,
V.S., Boulougoura, M., Wadge, E., Lygouras, J.N., The usage of soft-computing
methodologies in interpreting capsule endoscopy, Engineering Applications of
Artificial Intelligence, 20 (4), pp. 539-553, 2007.
-
Kosba,
E., Dimitrova, V., Boyle, R., Adaptive feedback generation to support teachers in
web-based distance education, User Modelling and User-Adapted Interaction, 17
(4), pp. 379-413, 2007.
-
Kranzusch
K.M., Abort determination with non-adaptive neural networks for the Mars
precision landers, Acta Astronautica (2007), doi: 10.1016/j.actaastro.2006.12.021
-
Kurubacak,
G., Building knowledge networks through project-based online learning: A study
of developing critical thinking skills via reusable learning objects, Computers
in Human Behavior, 23 (6), pp. 2668-2695, 2007.
-
Laskari,
Elena C., Meletiou, G.C., Stamatiou, Y.C., Vrahatis, M.N., Cryptography and
cryptanalysis through computational intelligence, Studies in Computational
Intelligence, 57, pp. 1-49, 2007.
-
Laskari,
E.C., Meletiou, G.C., Stamatiou, Y.C., Tasoulis, D.K., Vrahatis, M.N., Assessing
the effectiveness of artificial neural networks on problems related to elliptic
curve cryptography, Mathematical and Computer Modelling, 46 (1-2), pp. 174-179.
2007.
-
Lei,
T., Yang, Y., Aesthetic preference based on users' cognitive styles in mobile
interaction, Journal of Computational Information Systems, 3 (2), pp. 533-539,
2007.
-
Liang,
J.S., Evaluation of inspection ability promotion for learning mechanical
product Web-based inspection course in CAD education, Computer-Aided Design and
Applications, 4 (1-6), pp. 449-458, 2007.
-
Liu
W.-B., Wang X.-J., An evolutionary game based particle swarm optimization
algorithm, J. Comput. Appl. Math., 2007, doi: 10.1016/j.cam.2007.01.028
-
Lonnie
Hamm, Wade Brorsen B., Martin Hagan T., Comparison of Stochastic Global
Optimization Methods to Estimate Neural Network Weights, Neural Processing
Letters, 2007, doi: 10.1007/s11063-007-9048-7.
-
Mangal
M., Singh P. Analysis of pattern classification for the multidimensional
parity-bit-checking problem with hybrid evolutionary feed-forward neural
network, Neurocomputing, vol. 70(7-9), 1511-1524, 2007.
-
Mandal,
S., Sivaprasad, P.V., Venugopal, S., Capability of a feed-forward artificial
neural network to predict the constitutive flow behavior of as cast 304
stainless steel under hot deformation, Journal of Engineering Materials and
Technology, Transactions of the ASME, 129 (2), pp. 242-247, 2007.
-
Milosevic,
D., Brkovic, M., Sendelj, R., LeMONT: An ontology-based learner modeling
system, WSEAS Transactions on Computers, 6 (3), pp. 455-462, 2007.
-
Danchenko,
P., Lifshits, F., Orion, I., Koren, S., Solomon, A.D., Mark, S., NNIC-neural
network image compressor for satellite positioning system, Acta Astronautica,
60 (8-9), pp. 622-630, 2007.
-
Han
Yanfang, Shi Pengfei, An adaptive level-selecting wavelet transform for texture
defect detection, Image and Vision Computing, vol. 25(8), 1239-1248, 2007.
-
Guang-Bin
Huang; Qin-Yu Zhu; Mao, K.Z.; Chee-Kheong Siew; Saratchandran, P.;
Sundararajan, N.; Can threshold networks be trained directly? IEEE Transactions
on Circuits and Systems II: Analog and Digital Signal Processing, vol. 53, no.
3, pp.187-191, 2006.
-
Liu
Danyu, Cao Yu, Kim Ki-Hwan, Stanek Sean, Doungratanaex-Chai Bancha, Lin Kungen,
Tavanapong Wallapak, Wong J., Oh JungHwan and de Groen P. C. Arthemis:
Annotation software in an integrated capturing and analysis system for
colonoscopy, Computer Methods and Programs in Biomedicine (2007),
doi:10.1016/j.cmpb.2007.07.011
-
Parrott,
D.; Xiaodong Li; Locating and tracking multiple dynamic optima by a particle
swarm model using speciation, IEEE Transactions on Evolutionary Computation,
vol. 10, no. 4, pp.440-458, 2006.
-
del
Puerto Paule Ruiz M, Jesús Fernández Díaz M, Ortín Soler Francisco, and Pérez
Pérez J. R., Adaptation in current e-learning systems, Computer Standards &
Interfaces (2007), doi:10.1016/j.csi.2007.07.006
-
Kodogiannis
V. S., Decision support systems in Wireless Capsule Endoscopy: Revisited,
Intelligent Decision Technologies 1 (2007) 17–31 17.
-
Ruan,
X., Ding, M., Gong, D., Qiao, J., On-line adaptive control for inverted
pendulum balancing based on feedback-error-learning, Neurocomputing, 70 (4-6),
pp. 770-776, 2007.
-
Ridgway,
G.R., Godsill, S.J., Bayesian image modeling of cDNA microarray spots, IEEE Signal
Processing Letters, 14 (10), pp. 653-656, 2007.
-
Serban,
N., MICE: Multiple-peak identification, characterization, and estimation,
Biometrics, 63 (2), pp. 531-539+638, 2007.
-
Stathacopoulou
R., Grigoriadou M., Samarakou M., Mitropoulos D., Monitoring students' actions
and using teachers' expertise in implementing and evaluating the neural
network-based fuzzy diagnostic model, Expert Systems with Applications 32 (4),
pp.955-975, 2007.
-
Wang,
T.H., What strategies are effective for formative assessment in an e-learning
environment? Journal of Computer Assisted Learning, 23 (3), pp. 171-186, 2007.
-
Wang
Wan-liang, Tang Yu, The state of art in particle swarm optimization algorithms,
Journal of Zhejiang University of Technology, vol.35, no.2, 136-141, 2007.
-
Wang,
Y.-J., Zhang, J.-S., An efficient algorithm for large scale global optimization
of continuous functions, Journal of Computational and Applied Mathematics, 206
(2), pp. 1015-1026, 2007.
-
Yeh,
I-Cheng, Analysis-adjustment-synthesis networks, Connection Science, 19(3),
261–277, 2007.
-
Yang
Fang-Ying and Tsai Chin-Chung, Investigating university student preferences and
beliefs about learning in the web-based context, Computers & Education
(2007), doi:10.1016/j.compedu.2006.12.009
-
Yan
Jiang, Tiesong Hu, ChongChao Huang, Xianing Wu, An improved particle swarm
optimization algorithm, Appl. Math. Comput., vol.
193(1), 231-239, 2007.
-
Yoo,
S.J., Park, J.B., Choi, Y.H., Indirect adaptive control of nonlinear dynamic
systems using self recurrent wavelet neural networks via adaptive learning
rates, Information Sciences, 177 (15), pp. 3074-3098, 2007.
-
Yu
Min, Xu Wenbo, Sun Jun, Application of QPSO algorithm based on repulsion
technique in Nash equilibria, Computer Engineering and Applications, vol.43,
no.7, 31-33, 2007.
-
Zhang
Xuejun, Harding J., Personalised online sales using web usage data mining,
Computers in Industry, vol. 58(8-9), 772-782, 2007.
-
Le
Han, Gaohang Yu, Lutai Guan, Multivariate spectral gradient method for
unconstrained optimization, Applied Mathematics and Computation (2008),
doi:10.1016/j.amc.2007.12.054
-
Macklin
P.,·Lowengrub J.S., A New Ghost Cell/Level Set Method for Moving Boundary
Problems: Application to Tumor Growth, Journal of Scientific Computing (2008),
doi: 10.1007/s10915-008-9190-z
-
Passaro
A., Starita A., Particle Swarm Optimization for Multimodal Functions: a
Clustering Approach, Journal of Artificial Evolution and Applications (2008), http://www.hindawi.com/journals/jaea/aip.482032.html
-
Zhihua
Ruan, Huiming Wang, Yanrong Ren, Yongwen Chen, Junfeng Han, Xueli Pang, Houjie
Liang,Yuzhang Wu, Pseudo receptor probes: A novel pseudo receptor-based QSAR
method and application into studies on a new kind of selective vascular
endothelial growth factor-2 receptor inhibitors: Chemometr. Intell. Lab. Syst.
(2008), doi:10.1016/j.chemolab.2008.02.007
-
Chen
M. J., Wu B. and Chen C., Determination of shortest distance to voltage
instability with particle swarm optimization algorithm, Euro. Trans. Electr.
Power (2008), vol. 19, no. 8, 1109–1117, 2009.
-
Das,
R., Turkoglu, I., Sengur, A., Effective diagnosis of heart disease through
neural networks ensembles, Expert Systems with Applications, vol. 36, no. 4,
7675 – 7680, 2009.
-
Mandal
S., Sivaprasad P.V., Venugopal S., Murthy K.P.N, Artificial neural network
modeling to evaluate and predict the deformation behavior of stainless steel
type AISI 304L during hot torsion, Applied Soft Computing, vol. 9, no. 1,
237-244, 2009.
-
Tsallis,
C., Computational applications of nonextensive statistical mechanics, Journal
of Computational and Applied Mathematics, vol. 227, no.1, 51 – 58, 2009.
-
Yuan
G. and Wei Z., New line search methods for unconstrained optimization, Journal
of the Korean Statistical Society, vol. 38, no. 1, pp. 29–39, 2009.
-
Menéndez
de Llano, R., Bosque, J.L., Study of neural net training methods in parallel
and distributed architectures, Future Generation Computer Systems, vol.26, no.
2, 267 – 275, 2010.
-
Epitropakis,
M.G., Plagianakos, V.P., Vrahatis, M.N., Hardware-friendly Higher-Order Neural
Network Training using Distributed Evolutionary Algorithms, Applied Soft
Computing Journal, vol. 10, no. 2, 398 – 408, 2010.
-
Akbulut,
Y., Cardak, C.S, Adaptive educational hypermedia accommodating learning styles:
A content analysis of publications from 2000 to 2011, Computers and Education,
vol. 58, no. 2, pp. 835 – 842, 2012.
-
García-Cuesta,
E., Iglesias, J.A., User modeling: Through statistical analysis and subspace
learning, Expert Systems with Applications, vol. 39, no. 5, pp. 5243 – 5250,
2012.
-
Özyurt,
Ö., Özyurt, H., Baki, A., Güven, B., Karal, H.,
Evaluation of an adaptive and intelligent educational hypermedia for enhanced
individual learning of mathematics: A qualitative study, Expert Systems with
Applications, vol. 39, no. 15, pp. 12092 – 12104, 2012.
Home - Teaching - Publications - Bio - Blog - Department
In
books, edited volumes and PhD dissertations
-
Tzafestas
S.G. and Anthopoulos Y., Supervised learning in multilayer perceptrons: the
back-propagation algorithm. In Soft Computing in Systems and Control
Technology, World Scientific Series in Robotics and Intelligent Systems, Vol.
18, Chapter 1, S.G. Tzafestas (ed.), World Scientific, Singapore, August 1999,
pp.3-30 [ISBN: 9810233817].
-
Alexopoulos
S., Μια κλάση
αλγορίθµων
µε την ιδιότητα της
συζυγίας
για τη
βελτιστοποίηση µη
γραµµικών
συναρτήσεων
χωρίς
περιορισµούς (A class of algorithms with the conjugate property for
unconstrained optimization of nonlinear functions), PhD dissertation,
Department of Mathematics, University of Patras, 1999.
-
Gallagher
M. R., Multi-layer Perceptron Error Surfaces: Visualization, Structure and
Modelling, PhD dissertation, Department of Computer Science and Electrical
Engineering, University of Queensland, St Lucia 4072, Australia, January, 2000.
-
van den Bergh F., An analysis of particle swarm
optimisers, PhD dissertation, University of Pretoria, November 2001.
-
Manioudakis
G., Αλγόριθµοι µάθησης
µε εφαρµογή σε αναγνώριση δυναµικών συστη µάτων (Learning algorithms with
application to dynamic systems recognition), PhD dissertation,
Department of Computer Engineering and Informatics, University of Patras, 2001.
-
Skurichina
M .,Stabilizing weak classifiers PhD thesis
Quantitative Imaging Group Department of Imaging Science and Technology Faculty
of Applied Sciences Delft University of Technology Delft The Netherlands,
October 15, 2001.
-
Buendia
F. and Diaz P. A Framework for Educational Adaptive Hypermedia Applications.
Ιn: P. De Bra, P. Brusilovsky, and R. Conejo (eds.): Adaptive Hypermedia
and Adaptive Web-based Systems. Lecture Notes in Computer Science, Vol. 2347,
476-479. Berlin Heidelberg: Springer-Verlag, 2002.
-
Carlisle,
A.J., Applying the Particle Swarm Optimizer to Non-Stationary Environments, PhD
thesis, Auburn University, USA, 2002.
-
Coello
Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B., Evolutionary Algorithms for
Solving Multi-Objective Problems, Springer, 2002, ISBN: 0306467623.
-
Chen
Z .,Li J .,Yue Y .,Gao Q .,Zhao H .and Xu Z ., A neural network online training
algorithm based on compound gradient vector. In R.I .McKay and J. Slaney (Eds .):AI 2002, Lecture Notes in Computer Science (LNAI),
vol. 2557, pp .374-384,Springer-Verlag Berlin Heidelberg 2002.
-
Fukuyama,
Y., Fundamentals of Particle Swarm Techniques. In Lee K.Y. and El-Sharkawi M.A.
(eds.), Modern Heuristic Optimization techniques with Applications to Power
Systems, chapter 5, pp. 45-51, IEEE Power Engineering Society (PES) 2002. Also
available on-line at
http://homepage2.nifty.com/fukuyama-yoshikazu/ECTutorial.htm
-
Buckner,
M.A., Learning from Data with Localized Regression and Differential Evolution,
Ph.D. Thesis, University of Tennessee, Knoxville, USA, 2003.
-
Tasoulis
D.K., Spyridonos P., Pavlidis N.G., Cavouras D., Ravazoula P., Nikiforidis G.
and Vrahatis M.N., Urinary bladder tumor grade diagnosis using on-line trained
neural networks, Lecture Notes in Computer Science (LNAI), 2773, October 2003,
pp.199-206.
-
Chen
Z., Dong Ch., Zhou Q. and Zhang Sh., An improved compound gradient vector based
neural network on-line training algorithm P .W. H. Chung C .J .Hinde M .Ali (eds .), IEA /AIE 2003, Lecture Notes in Computer Science,
(LNAI) 2718 pp 316-325, Springer-Verlag Berlin Heidelberg 2003.
-
Karagiozov
V., Artificial Neural Networks: Enhanced Back Propagation in Character
Recognition, in Information Technology & Organizations: Trends, Issues,
Challenges & Solutions, Mehdi Khosrow-Pour (ed.), Information Resources
Management Association, USA, pp. 263-265, 2003.
-
Sirlantzis
K .,Algorithmic synthesis in neural network training
for pattern recognition. In Pattern Recognition and String Matching Series :Combinatorial Optimization vol 13, D. Chen and X.
Cheng (eds.), Kluwer Academic Publishers Dordrecht, pp .703–739, 2003 [ISBN
:1-4020-0953-4 ].
-
Tasoulis
D.K., Vladutu L., Plagianakos V.P., Bezerianos A., and Vrahatis M.N., On-line
neural network training for automatic ischemia episode detection. In Leszek
Rutkowski, Jörg H. Siekmann, Ryszard Tadeusiewicz, and Lotfi A. Zadeh, editors,
Lecture Notes in Computer Science, 3070:1062-1068. Springer-Verlag, 2004.
-
Fieldsend,
J.E., Novel Algorithms for Multi-Objective Search and their Application in
Multi-Objective Evolutionary Neural Network Training, PhD thesis, University of
Exeter, U.K, 2004.
-
Mendes,
R., Population Topologies and their Influence in Particle Swarm Performance,
PhD thesis, Departamento de Informatica, Escola de Engenharia, Universidade do
Minho, Portugal, 2004.
-
Krusienski,
D.J., Enhanced Structured Stochastic Global Optimization Algorithms for IIR and
Nonlinear Adaptive Filtering, PhD thesis, Department of Electrical Engineering,
The Pennsylvania State University, USA, August 2004.
-
Chen
Z., Chen X., Zhang J. and Liu L., Convergence analysis of a neural network
based on generalised compound gradient vector, B. Orchard, Ch. Yang, M. Ali
(eds.): IEA /AIE 2004, Lecture Notes in Computer Science (LNAI ), vol. 3029,
pp. 1174–1183, Springer-Verlag Berlin Heidelberg, 2004.
-
Petalas,
Y.G., Tasoulis, D.K., Vrahatis, M.N., Dynamic search trajectory methods for
neural network training, Lecture Notes in Artificial Intelligence, vol. 3070,
pp. 241-246, 2004.
-
Vladutu
L., Computational intelligence methods on biomedical signals analysis and data
mining in medical records, PhD thesis, Department of Medical Physics School of
Medicine University of Patras, Patras, Greece, 2004.
-
Zhang
X.-J., An effective design method for components made of a multiphase perfect
material, PhD thesis, Department of Mechanical Engineering, The University of
Hong Kong, Hong Kong, 2004.
-
Encheva,
S., Tumin, S., Cooperative shared learning objects in an intelligent web-based
tutoring environment, Lecture Notes in
Computer Science, vol. 3675, pp. 227-234, 2005.
-
Lee,
J., Jun, W., Design and implementation of a web-board system for the adaptive
school web site construction, Lecture Notes in Computer Science, vol. 3807, pp.
94-103, 2005.
-
Engelbrecht,
A.P., Fundamentals of Computational Intelligence, Wiley, 2005 [ISBN:
0-470-09191-6].
-
Schmitt
S., The diamond operator implementation of exact real algebraic numbers,
Lecture Notes in Computer Science, 3718, pp. 355-366, 2005.
-
Schoeman,
L., Engelbrecht, A.P., A Parallel Vector-Based Particle Swarm Optimizer, in
Adaptive and Natural Computing Algorithms, Proc. International Conference on
Artificial Neural Networks and Genetic Algorithms (ICANNGA 2005), Portugal, B
.Ribeiro R.F., Albrecht A .Dobnikar D .W .Pearson and N .C. Steele (eds .),
Springer -Verlag New York, pp. 268–271 [ISBN :3-211-24934-6 ]
-
Anastasiadis
A, Neural network training and applications using biological data, PhD thesis,
Birkbeck College, University of London, 2006.
-
Brusilovsky,
P., Sosnovsky, S., Yudelson, M., Addictive links: The motivational value of
adaptive link annotation in educational hypermedia, Lecture Notes in Computer
Science, vol. 4018, pp. 51-60, 2006.
-
Bull,
S., Mabbott, A., 20000 inspections of a domain-independent open learner model
with individual and comparison views, Lecture Notes in Computer Science, vol.
4053, pp. 422-432, 2006.
-
Herrera
B.M., Ribas L., dos Santos Coelho L. Nonlinear identification method of a yo-yo
system using fuzzy model and fast particle swarm optimization. In Applied Soft
Computing Technologies: The Challenge of Complexity, Ajith Abraham, Bernard de
Baets, Mario Köppen and Bertram Nickolay, (eds.), Advances in Soft Computing
Series, Springer, pp. 303-314, 2006.
-
Kelly,
D., Tangney, B., Using multiple intelligence informed resources in an adaptive
system, Lecture Notes in Computer Science, vol. 4053, pp. 412-421, 2006.
-
Li
J., Learning Reactive Behaviors with Constructive Neural Networks in Mobile
Robotics, PhD thesis, Orebro University, Orebro Studies in Technology 23,
Sweden 2006 [ISSN 1651-8896] [ISBN 91-7668-490-3]. Available online at:
www.diva-portal.org/diva/getDocument?urn_nbn_se_oru_diva-629-2__fulltext.pdf
-
Nguyen
M.-H., Cooperative Coevolutionary Mixture of Experts: A Neuro Ensemble Approach
of Automatic Decomposition of Classification Problems, PhD thesis, School of
Information Technology and electrical Engineering, Australian Defence Force
Academy, University of New South Wales, Sydney, Australia, February 2006.
http://www.library.unsw.edu.au/~thesis/adt-ADFA/uploads/approved/adt-ADFA20061024.142217/public/
-
Garcia-Palomares,
U.M., Non monotone algorithms for unconstrained minimization: upper bounds on
function values. In System Modeling and Optimization, vol. 199, Ceragioli F.,
Dontchev A, Furuta H., Marti K., Pandolfi L. (eds), IFIP International
Federation for Information Processing, Springer, pp. 91-100, 2006.
-
Pritchard
D., Negoita M.Gh., A fuzzy-Ga hybrid technique for optimization of teaching
sequences presented in ITSs, In Computational Intelligence, Theory and
Applications: Proc 8th International Conference Fuzzy Days in Dortmund,
Germany, Sept. 29–Oct. 01, 2004, Bernd Reusch (ed.), Advances in Soft Computing
Series, Springer, pp. 311-316, 2006.
-
O'Keeffe,
I., Conlan, O., Wade, V., A unified approach to adaptive hypermedia
personalisation and adaptive service composition, Lecture Notes in Computer
Science, vol. 4018, pp. 303-307, 2006.
-
Schoeman
I., Engelbrecht A., Niching for dynamic environments using particle swarm
optimization. In Tzai-Der Wang, Xiaodong Li, Shu-Heng Chen, Xufa Wang, Hussein
A. Abbass, Hitoshi Iba, Guoliang Chen and Xin Yao (eds.), Simulated Evolution
and Learning, Lecture Notes in Computer Science, vol.4247 LNCS, 2006, pp.
134-141.
-
Spyridonos,
P., Vilarino, F., Vitria, J., Azpiroz, F., Radeva, P., Anisotropic feature
extraction from endoluminal images for detection of intestinal contractions,
Lecture Notes in Computer Science vol. 4191, Proc. 9th International Conference
on Medical Image Computing and Computer Assisted Intervention, pp. 161-168,
2006.
-
Tar
JK, Rudas IJ, Szeghegyi A, Kozlowski K., Novel adaptive control of partially
modeled dynamic systems, Robot Motion and Control: Recent Developments, Lecture
Notes in Control and Information Sciences, vol. 335, 99-111, 2006.
-
Wang,
Z., Cao, Y., Short-term load forecasting based on mutual information and
artificial neural network, Lecture Notes in Computer Science, vol. 3972, pp.
1246-1251, 2006.
-
Wikstrand
G., Human Factors and Wireless Network Applications: More Bits and Better Bits,
PhD thesis, Department of Computing Science, Umea University, UMINF 06.34, Umea
2006 [ISSN 0348–0542] [ISBN 91–7264–205–X]. Available online at:
www.diva-portal.org/diva/getDocument?urn_nbn_se_umu_diva-910-2__fulltext.pdf
-
Du
K.-L. and Swamy M.N.S., Neural Networks in a Soft Computing Framework,
Springer, London, April 2006, ISBN: 1-84628-302-7
-
Sae
Hwang, Automatic Content Analysis of Endoscopy Video: Endoscopic Multimedia
Information System, PhD thesis, The University of Texas at Arlington, May 2007.
-
Fernando
Vilari, Gerard Lacey, Jiang Zhou, Hugh Mulcahy, and Stephen Patchett, Automatic
Labeling of Colonoscopy Video for Cancer Detection, J. Martı et al.
(Eds.): IbPRIA 2007, Part I, Lecture Notes in Computer Science, vol. 4477, pp.
290–297, Springer-Verlag Berlin Heidelberg 2007
-
Chen
Guolong, Chen Qingliang, and Guo Wenzhong, A PSO-Based
Approach to Rule Learning in Network Intrusion Detection, B.-Y. Cao (Ed.):
Fuzzy Information and Engineering (ICFIE), ASC 40, pp. 666–673, Springer-Verlag
Berlin Heidelberg 2007
-
Hui
Wang, Sanyou Zeng, Yong Liu, Wenjun Wang, Hui Shi, and Gang Liu,
Re-diversification Based Particle Swarm Algorithm with Cauchy Mutation, in L.
Kang, Y. Liu, and S. Zeng (Eds.): ISICA 2007, Lecture Notes in Computer Science
book series, vol. 4683, pp. 362–371, 2007.
-
Iakovidis
D. K., Savelonas M. A., and Maroulis D., Adaptive Vision System for
Segmentation of Echographic Medical Images Based on a Modified Mumford-Shah
Functional, in J. Blanc-Talon et al. (Eds.): ACIVS 2007, Lecture Notes in
Computer Science book series, vol. 4678, pp.565–574, 2007.
-
Xinmei
Liu, Jinrong Su, and Yan Han, An Improved Particle
Swarm Optimization for Traveling Salesman Problem, in D.-S. Huang, L. Heutte,
and M. Loog (Eds.):ICIC 2007, Lecture Notes in Artificial
Intelligence series, vol. 4682, pp. 803–812, 2007.
-
Khosrow
Kaikhah, A New Hybrid Learning Algorithm for Drifting Environments, H.G. Okuno
and M. Ali (Eds.): IEA/AIE 2007, Lecture Notes in Artificial Intelligence
series, vol. 4570, pp. 705–714, 2007.
-
Bumghi
Choi, Ju-Hong Lee, and Tae-Su Park, Dual Gradient Descent Algorithm on
Two-Layered Feed-Forward Artificial Neural Networks, in H.G. Okuno and M. Ali
(Eds.): IEA/AIE 2007, Lecture Notes in Artificial Intelligence series, vol.
4570, pp. 696–704, 2007.
-
Stefan
Duffner and Christophe Garcia, An Online Backpropagation Algorithm with
Validation Error-Based Adaptive Learning Rate, J. Marques de Sá et al. (Eds.):
ICANN 2007, Part I, Lecture Notes in Computer Science series, vol. 4668, pp.
249–258, 2007.
-
Stefan
Duffner, Face Image Analysis With Convolutional Neural Networks, PhD thesis,
Albert-Ludwigs-Universitat Freiburg im Breisgau, 2007.
-
Jiang
Yan, Hu Tiesong, Huang Chongchao, Wu Xianing, and Gui Faling, A Shuffled
Complex Evolution of Particle Swarm Optimization Algorithm, in B. Beliczynski
et al. (Eds.): ICANNGA 2007, Part I, Lecture Notes in Computer Science series,
vol. 4431, pp. 341–349, 2007.
-
Jian-Xun
Peng; Kang Li; Irwin, G.W.; A New Jacobian Matrix for Optimal Learning of
Single-Layer Neural Networks, IEEE Transactions on Neural Networks, vol. 19,
no. 1, pp.119-129, 2008.
-
Zhao
Zhongyu; Wenfang Xie; Herry Hong, Identification of Takagi-Sugeno (TS) fuzzy
model with Evolutionary Parallel Gradient Search, Proc. Annual Meeting of the
North American Fuzzy Information Processing Society (NAFIPS-2008), pp. 1 – 6,
2008.
Home - Teaching - Publications - Bio - Blog - Department
In
conference and workshop proceedings
-
Engelbrecht
A .P .and Cloete I .,Selective learning using
sensitivity analysis In :IEEE World Congress on Computational Intelligence,
International Joint Conference on Neural Networks Anchorage Alaska May 4 –9, pp
.1150 –1155,1998.
-
Kumar
D .N .and Sathish T ., Forecasting hydrologic time series using artificial
neural networks, Proc. of the International Conference on Theoretical ,Applied
,Computational and Experimental Mechanics Kharagpur India December 1 –5, 1998.
-
Manioudakis
G .D .,Demiris E .N .and Likothanassis S .D .,A self -organized neural network
based on the multi-model partitioning theory, Proc. of the World
Multiconference on Systems, Cybernetics and Informatics, Communication Systems
Internet and Mobile /Wireless Computing, vol .4 Orlando Florida USA, July 31
–August 4,1999.
-
Tar,
J.K.; Rudas, I.J.; Kozlowski, K.; Bito, J.F., Dynamic parameter tuning in a
particular branch of soft computing specially designed for mechanical systems'
control, Proc. of the 25th Annual Conference of the IEEE Industrial Electronics
Society (IECON '99), vol.2, pp.1002-1007, 1999.
-
Chambers
J .A ., Sherliker W .and Mandic D .P ., A normalized
gradient algorithm for an adaptive recurrent perceptron, Proc. of the IEEE
International Conference on Acoustics ,Speech and Signal Processing (ICASSP
’00), Istanbul Turkey vol .1 pp .396 –399, 2000.
-
Dawson
CW., Wilby RL., Harpham C. and Brown MR., Modelling Ranunculus Presence in the
Rivers Test and Itchen Using Artificial Neural Networks, Proceedings of
GeoComputation 2000, University of Greenwich, UK.
-
Atkinson,
C., Eldabi, T., Paul, R.J. and Pouloudi, A., The Centre for Health
Informatics and Computing (CHIC). Proceedings of the 22nd International
Conference on Information Technology Interfaces (ITI '2000), D. Kalpic &
V.H. Dobric (Eds.), pp. 3-21, SRCE University Computing Centre, University of
Zagreb, June 13-16, 2000, Pula, Croatia.
-
Atkinson
C., Eldabi T., Paul R.J., and Pouloudi A., Investigating integrated
socio-technical approaches to health informatics, Proc. of the 34th Annual
Hawaii International Conference on System Sciences, Jan 3-6 2001, 10 pp.
-
Golovko
V., Savitsky Y., Laopoulos T., Sachenko A. and Grandinetti L., Technique for
learning rate estimation for efficient training of MLP, Proc. IEEE
International Joint Conference on Neural Networks, Como, Italy, July 24 –27,
2000, vol .1, pp .1323 –1330, 2000.
-
Hu,
X., Eberhart, R., Tracking Dynamic Systems with PSO: Where's the Cheese?, Particle Swarm Optimization Workshop, April 6-7, 2001,
Indianapolis, Indiana, U.S.A, pp.80-83, 2001.
-
Karkanis,
S.A., Iakovidis, D.K., Karras, D.A., Maroulis, D.E., Detection of lesions in
endoscopic video using textural descriptors on wavelet domain supported by
artificial neural network architectures, IEEE International Conference on Image
Processing, 2, pp. 833-836, 2001.
-
Lee
C-S, Singh, Y.P. A Case-based Agent Framework for Adaptive Learning. IEEE
International Conference on Advanced Learning Technologies, paper-id 095,
Madison, Wisconsin, August 2001.
-
Mizutani
E., Dreyfus S., On the complexity analysis of
supervised MLP-learning for algorithmic comparisons, Proc. IEEE International
Joint Conference on Neural Networks, Washington, USA, Vol .1, pp. 347–352,
2001.
-
Brusilovsky
P., Adaptive Educational Hypermedia. Proceedings of 10th International PEG
Conference: Intelligent Computer and Communication Technology-Learning in
online communities, Tampere, Finland, June 23-26, 2001, pp. 8-12.
-
Eberhart,
R.C., Shi, Y., Particle Swarm Optimization: Developments, Applications and Resources,
Proceedings of the IEEE Congress on Evolutionary Computation, (CEC 2001),
Seoul, Korea, May 27-30, 2001, pp.81-86.
-
Tar,
J.K., Rudas, I.J., Bito, J.F., Andersson, P.H., Torvinen, S.J., Structurally
and procedurally simplified soft computing for real time control, Proc. IEEE
International Conference on Robotics and Automation (ICRA), vol.2, pp.
2002-2007, 2001.
-
Kawaji
S., AraoM. and ChenY., Thrust force control of
drilling system using neural network, Proceedings of the IEEE/ASME
International Conference on Advanced Intelligent Mechatronics (AIM 2001), Vol.
1, pp.476-481, 2001.
-
Kontoni P.N. and
Petropoulos P.N. Οι υπηρεσίες του διαδικτύου ως εκπαιδευτικά εργαλεία για την από απόσταση συμπληρωματική εκπαίδευση αποφοίτων Α.Ε.Ι. και Τ.Ε.Ι. Proceedings
of the 1st Hellenic Conference on Open and Distance Learning (CD-ROM Proceedings), May, Patras,
Greece 2001.
-
Prenztas D. Hatziligeroudis I., Koutsogiannis K., Rigou M., H
Αρχιτεκτονική
ενός Ευφυούς
Συστήματος
Βασισμένο στο
Διαδίκτυο για
τη Διδασκαλία
Νέων Τεχνολογιών
Πληροφορικής. Proceedings of the 1st Hellenic
Conference on Open and Distance Learning (CD-ROM Proceedings), May, Patras, Greece 2001.
-
Prenztas D. Hatziligeroudis I.,
Προσαρμοστικά
Εκπαιδευτικά
Υπερμέσα:
Αρχές και
Υπηρεσίες. Proceedings of the 1st Hellenic
Conference on Open and Distance Learning (CD-ROM Proceedings), May, Patras, Greece 2001.
-
Lin
X .-B .,Zhang Z .-L .,Ruan X .-Y .,Prediction of material flow stress in warm
forging with BP neural network, Shanghai Jiaotong Daxue Xuebao /Journal of
Shanghai Jiaotong University, 36(4), 459 –462, 2002.
-
Meletiou
G.C., Tasoulis D.K, and Vrahatis M.N., A first study of the neural network
approach to the RSA cryptosystem, In Proceedings of the IASTED 2002 Conference
on Artificial Inteligence, pages 483-488, 2002.
-
Bull,
S. and Nghiem, T.: Helping Learners to Understand Themselves with a Learner
Model Open to Students, Peers and Instructors. In: P. Brna & V. Dimitrova (eds): Proceedings of Workshop on Individual and Group
Modeling Methods that Help Learners Understand Themselves, International
Conference on ITS2002, pp. 5-13.
-
Brits,
R., Engelbrecht, A.P., Van den Bergh, F., A Niching Particle Swarm Optimizer,
4th Asia-Pacific Conference on Simulated Evolution and Learning, 2002.
-
El-Gallad,
A., El-Hawary, M., Sallam, A., Kalas, A., Enhancing the Particle Swarm
Optimizer via Proper Parameters Selection, Canadian Conference on Electrical
and Computer Engineering, Vol. 2, pp. 792-797, 2002
-
Annunziato
M., Lucchetti M. and Pizzuti S., Adaptive Systems and Evolutionary Neural
Networks: a Survey, Proc. of European Symposium on Intelligent Technologies,
Hybrid Systems and their Implementation on Smart Adaptive Systems (EUNITE
2002), 19-21 September 2002, Albufeira, Portugal, pp. 606-610.
-
Tar,
J.K., Rudas, I.J., Bito, J.F., Kozlowski K., A new approach in computational
cybernetics based on the modified renormalization algorithm guaranteeing
complete stability in the control of a wide class of physical systems, Proc.
6th IEEE International Conference on Intelligent Engineering Systems
(INES2002), May 26-28, Opatija, Croatia, pp. 19-24, 2002 [ISBN 953-6071-17-7].
-
Patkai
B., Tar, J.K., Rudas, I.J., Bito, J.F., Convergence properties of the modified
renormalization algorithm based adaptive control supported by ancillary methods,
Proc. of the 2002 IEEE International Symposium on Industrial Electronics (ISIE
2002), vol .2, pp .441 –446,2002.
-
Parsopoulos,
K.E., Vrahatis, M.N., Particle swarm optimization method in multiobjective
problems, Proceedings of the ACM Symposium on Applied Computing, pp.603-607,
2002.
-
King,
H., Garibaldi, J. and Rogerson, S., Intelligent medical systems: partner or
tool? Proc of the 6th International Conference: The transformation of
organizations in the information age: social and ethical implications-ETHICOMP
02, 13-15 November, Lisbon, Portugal, Alvarez, I. et al. (Eds.), pp. 181-190,
2002.
-
Manouselis,
N. and Sampson, D. Dynamic knowledge route selection for personalised learning
environments using multiple criteria. In Proceedings of the 20th IASTED International
Multi-Conference Applied Informatics (AI 2002). Innsbruck, Austria, February
18-21, 2002.
-
Abdel
Razek M., Frasson C. and Kaltenbach M. Towards More
Cooperative Intelligent Distance Learning Environments. SACHA 2002 (Software
Agents - Cooperation – Human Activity) Workshop at ITS2002, June 2002, San
Sebastian Spain, 2002.
-
Abdel
Razek M., Frasson C. and Kaltenbach M. Using Machine Learning approach To
Support Intelligent Collaborative Multi-Agent System. International Conference
on Technology of Information and Communication in Education for engineering and
industry (TICE 2002), 13-15 November 2002, Lyon, France, 2002.
-
Abdel
Razek M., Frasson C. and Kaltenbach M. A
Confidence Agent: Toward More Effective Intelligent Distance Learning
Environments. In Proceedings Of International
Conference on Machine Learning and Applications (ICMLA), Las Vegas, USA, June
24-27, 2002.
-
Cerqueira
J .J .F .,Palhares A .G .B .and Madrid M .K ., A simple adaptive
back-propagation algorithm for multi-layered feedforward perceptrons, Proc. of
the IEEE International Conference on Systems ,Man and Cybernetics, vol .3, pp.
590 –595, 2002.
-
Chen
Z .,Li J .,Zhao H .,Gao Q .,Yue Y .and Xu Z .,Online training of neural network
control for electric motor drives In :Proceedings of the IEEE International
Conference on Systems ,Man and Cybernetics Vol.2, pp 661-666, 2002.
-
Yu
Ch .and Manry M .T .,A modified hidden weight optimization algorithm for feed
-forward neural networks, Proc. of the IEEE 36th Asilomar Conference on
Signals, Systems, and Computers 2002, vol. .2, pp. 1034 –1038, 2002.
-
Iakovidis
D.K., Maroulis D.E., Karkanis S.A. and Flaounas I.N., Color texture recognition
in video sequences using wavelet covariance features and support vector
machines, Proc. 29th Euromicro Conference, 1-6 Sept. 2003, pp. 199-204.
-
Tsou
D. and MacNish C., Adaptive particle swarm optimisation for high-dimensional
highly convex search spaces, Proc. of the Congress on Evolutionary Computation
(CEC 2003), vol. 2, pp. 783 –789, December 8–12, 2003.
-
Birge,
B., PSOt-A Particle Swarm Optimization Toolbox for Use With Matlab, Proceedings
of the IEEE 2003 Swarm Intelligence Symposium (SIS 2003), April 24-26, 2003,
Indianapolis, Indiana, U.S.A., IEEE press 2003, pp. 182-186 [ISBN 0780379144].
-
Yudelson,
M.V., Yen, I.-L., Panteleev, E., Khan, L., A framework for an intelligent
on-line education system, ASEE Annual Conference Proceedings, pp. 4891-4906,
2003.
-
Zheng,
Y.-L., Ma, L.-H., Zhang, L.-Y., Qian, J.-X., Empirical Study of Particle Swarm
Optimizer with an Increasing Inertia Weight, Proceedings of the IEEE 2003
Congress on Evolutionary Computation, Canberra, Australia, pp. 221-226, 2003.
-
Zheng,
Y.-L., Ma, L.-H., Zhang, L.-Y., Qian, J.-X., On the Convergence Analysis and
Parameter Selection in Particle Swarm Optimization, Proceedings of 2003
International Conference on Machine Learning and Cybernetics, Xi-an, China,
Vol. 3, pp. 1802-1807, 2003.
-
Zheng
Y.-L., Ma L.-H., Zhang L.-Y. and Qian J.-X ., Robust PID controller design using
particle swarm optimizer, Proc. of the IEEE International Symposium on
Intelligent Control pp .974 –979, 2003.
-
Mendes,
R., Kennedy, J., Neves, J., Avoiding the Pitfalls of Local Optima: How
Topologies Can Save the Day, Proceedings of the 12th Conference Intelligent
Systems Application to Power Systems (ISAP2003), Lemnos, Greece, 2003, IEEE
Computer Society.
-
Li,
T., Wei, C., Pei, W., PSO With Sharing for Multimodal Function Optimization,
Proc. 2003 International Conference on Neural Networks and Signal Processing,
14-17 Dec. 2003, Nanjing, China, vol. 1, pp. 450-453, 2003
-
Brusilovsky,
P., Santic, T. and De Bra, P. A Flexible Layout Model for a Web-Based Adaptive
Hypermedia Architecture, Workshop on Adaptive Hypermedia and Adaptive Web-Based
Systems at the International World Wide Web Conference, Budapest, Hungary, May
20, 2003.
-
Bajraktarevic
N, Hall W. and Fullick P., Incorporating learning styles in hypermedia
environment: Empirical evaluation. Workshop on Adaptive Hypermedia and Adaptive
Web-Based Systems at the International World Wide Web Conference, Budapest,
Hungary, May 20, 2003.
-
Chen
Z., Lou R. and Zhao Y., Neural network control of electric machines for
transportation systems, Proc. of the IEEE International Conference on Systems
,Man and Cybernetics, vol. 2, pp. 1904–1909, 2003.
-
Chen
Z., Zhao H. and Wei K., Compound gradient vector based neural networks for
real-time control, Proc. of the IEEE Industry Applications Society 38th Annual
Meeting, October 12–16, 2003, Salt Lake City Utah USA, vol .2, 755–760, 2003.
-
Chermakani
D .P ., A novel approach for training small-sized multi-layer perceptrons,
Proc. of the International Joint Conference on Neural Networks (IJCNN 2003),
vol .3, pp.1999–2004, 2003.
-
Daqi
G., Hua L. and Changwu L., On variable sizes and
sigmoid activation functions of multilayer perceptrons, Proc. of the
International Joint Conference on Neural Networks (IJCNN 2003), vol. 3, pp.
2017–2022, 2003.
-
Lee
J., Global optimization for fast multilayer perceptron training, Proc. of the
International Joint Conference on Neural Networks (IJCNN 2003), vol. 1, pp.
410–414, 2003.
-
Papanikolaou
K.A. and Grigoriadou M., An instructional framework supporting personalized
learning on the Web, Proc. the 3rd IEEE International Conference on Advanced
Learning Technologies, 9-11 July 2003, pp. 120–124.
-
Parsopoulos
K.E. and Vrahatis M.N., Investigating the existence of function roots using
particle swarm optimization, Proc. of the 2003 Congress on Evolutionary
Computation (CEC '03), 8-12 Dec. 2003, vol. 2, pp. 1448-1455.
-
Parsopoulos
K.E. and Vrahatis M.N., Computing periodic orbits of
nondifferentiable/discontinuous mappings through particle swarm optimization,
Proc. of the 2003 IEEE Swarm Intelligence Symposium (SIS '03), 24-26 April
2003, pp. 34-41.
-
Pires
P.A.B.R., Evaluation of neural networks algorithms in marketing problems :an experimental approach, XIII Jornadas
Hispano-Lusas de Gestion Cientifica Lugo Spain, pp .263–272, 2003. Available
on-line at: http://www.ti.usc.es/lugo-xiii-hispano-lusas/04_programa.htm [last
accessed 17/11/06].
-
Barcelos
M., Bavestrello H. and Maute K., Efficient solution strategies for steady-state
aeroelastic analysis and design sensitivity analysis, Collection of Technical
Papers-10th AIAA /ISSMO Multidisciplinary Analysis and Optimization Conference,
vol .3, pp. 1954–1967, 2004.
-
Bedor,
H.S., Mohamed, H.K., Shedeed, H.A., A general architecture of student modelto
assess the learning performance in intelligent tutoring systems, Proceedings of
the International Conference on Electrical, Electronic and Computer Engineering
(ICEEC'04), pp. 173-178, 2004.
-
Bunt,
A., Conati, C., McGrenere, J., What role can adaptive support play in an
adaptable system? Proceedings of the International Conference on Intelligent
User Interfaces (IUI), pp. 117-124, 2004.
-
Goedtel,
A., Da Silva, I.N., Serni, P.J.A., An alternative approach to solve convergence
problems in the backpropagation algorithm, Proceedings of the IEEE
International Conference on Neural Networks, 2, pp. 1021-1026, 2004.
-
Hammouda
I., Guldogan O., Koskimies K. and Systa T., Tool-supported customization of UML
class diagrams for learning complex system models, Proc. 12th IEEE
International Workshop on Program Comprehension, 24-26 June 2004, pp. 24-33.
-
Hatzilygeroudis
I., Giannoulis C. and Koutsojannis C., A Web-based education system for
predicate logic, Proc. IEEE International Conference on Advanced Learning
Technologies, 30 Aug.-1 Sept. 2004, pp. 106-110.
-
Jordanov
I.N. and Rafik T.A., Local minima free neural network learning, Proc. of the 2nd
IEEE International Conference on Intelligent Systems, vol. 1, pp. 34 –39, 2004.
-
Pereira,
A., Fernandes, E., Reduction Method with Simulated Annealing for Semi-Infinite
Programming, 12th French-German-Spanish Conference on Optimization, Avignon,
France, page 98, 2004.
-
Karkanis,
S.A., Iakovidis, D.K., Maroulis, D.E., Color textural features under varying
illumination, Proceedings of the International Conference on Image Processing
(ICIP), 3, pp. 1505-1508, 2004.
-
Li
J., Manry M.T., Liu L.-M., Yu C. and Wei J., Iterative improvement of neural
classifiers, Proc. of the 7th International Florida Artificial Intelligence
Research Society Conference (FLAIRS 2004), vol. 2, pp .700–705, 2004.
-
Liu
Y., Qin Z. and He X.-S., Supervisor-student model in particle swarm optimization,
Proc. IEEE Congress on Evolutionary Computation 2004 (CEC 2004), Portland USA,
vol.1, ,pp. 542–547, IEEE, 2004.
-
Liu
Y., Qin Z., Xu Z.-L .and He X.-S., Using relaxation velocity update strategy to
improve particle swarm optimization, Proc. of the 2004 International Conference
on Machine Learning and Cybernetics, Shangai, China, vol .4, pp. 2469–2472,
2004.
-
Petalas
Y.G., Tasoulis D.K., and Vrahatis M.N., Trajectory methods for neural network
training, In M.H. Hamza, editor, Proceedings of the IASTED International
Conference on Artificial Intelligence and Applications (AIA 2004), pp. 400-403,
Innsbruck, Austria, 2004. IASTED/ACTA Press.
-
Yu
C., and Manry M.T., A Hessian matrix approach for training nonlinear networks,
Proc. International Conference on Signal Processing (ICSP), vol. 2,
pp.1514-1517, 2004.
-
Yu
C., Manry M.T. and Li J., Hidden layer training via Hessian matrix information,
Proc. of the 7th International Florida Artificial Intelligence Research Society
Conference (FLAIRS 2004), vol. 2, pp. 688–693, 2004.
-
Wu
Y., A novel link structure and learning algorithm of feedforward neural
network, Porc. International Conference on Signal Processing (ICSP), vol. 2,
pp.1534-1537, 2004.
-
Wu
Y. and Wang S., A new algorithm to improve the generalization capability of
feedforward neural network through network inversion, Proc. of the World
Congress on Intelligent Control and Automation (WCICA ),
vol. 3, pp. 1985–1988, 2004.
-
Liu,
Y., Qin, Z., He, X., Supervisor-Student Model in Particle Swarm Optimization,
Proceeding of the 2004 Congress on Evolutionary Computation, USA, pp. 542-547,
2004.
-
Parrott,
D., Li, X., A Particle Swarm Model for Tracking Multiple Peaks in a Dynamic
Environment Using Speciation, Proc. of the 2004 Congress on Evolutionary
Computation, USA, pp. 98-103, 2004.
-
Petalas,
Y.G., Vrahatis, M.N., Parallel tangent methods with variable stepsize, Proc.
IEEE International Conference on Neural Networks, 2, pp. 1063-1066, 2004.
-
Zhang,
Y., Ji, C., Yuan, P., Li, M., Wang, C., Wang, G., Particle Swarm Optimization
for Base Station Placement in Mobile Communication, Proceedings of 2004 IEEE
International Conference on Networking, Sensing and Control, 21-23 March, 2004,
Taipei, Taiwan, vol. 1, pp. 428-432, 2004.
-
Liu,
Y., Qin, Z., Xu, Z.-L., He, X.-S., Using Relaxation Velocity Update Strategy to
Improve Particle Swarm Optimization, Proceedings of 2004 International
Conference on Machine Learning and Cybernetics, Shangai, China, Vol. 4, pp.
2469-2472, 2004.
-
Schoeman,
I.L., Engelbrecht, A.P., Using Vector Operations to Identify Niches for
Particle Swarm Optimization, IEEE 2004 Conference on Cybernetics and
Intelligent Systems, pp. 361-366, 2004.
-
Tar
J.K., Rudas I.J. , Bitó J.F., Comparison of the Operation of the Centralized
and the Decentralized Variants of a Soft Computing Based Adaptive Control,
Budapest Tech Jubilee Conference: Science in Engineering, Economics and
Education, Budapest, Hungary, September 4, 2004.
-
Tar
J.K., Rudas U., Szeghegyi A. and Kozlowski K., Adaptive control of a dynamic
system having unmodeled and unconstrained internal degree of freedom, Proc. of
the 4th International Workshop on Robot Motion and Control (RoMoCo ’04), pp.
41–46, 2004.
-
Orion
F. Reyes-Galaviz and Carlos Alberto Reyes-Garcia, A System for the Processing
of Infant Cry to Recognize Pathologies in Recently Born Babies with Neural
Networks, Proceedings of the 9th Conference Speech and Computer (SPECOM 2004),
September 20-22, 2004, St. Petersburg, Russia, International Speech
Communication Association, ISCA Archive, 2004.
-
Ho
L.S. and Rajapakse J.C., High sensitivity technique for translation initiation
site detection, Proc. of the IEEE 2004 Symposium on Computational Intelligence
on Bioinformatics and Compuutational Biology (CIBCB ’04), pp. 153–159, IEEE
Press, 2004.
-
Jiang
M., Pang H., Deng B. and Zong C., A fast learning algorithm of neural network
for the training and recognition of the phonemes, Proc. of the International
Symposium on Intelligent Multimedia ,Video and Speech Processing (ISIMP 2004),
pp. 318–321, 2004.
-
Valaboju
S., Pulluri S., Davari A. and Shadle L., Real time modeling and control of
Circulating Fluidized Bed, Proc. of the 36th Southeastern Symposium on System
Theory, vol. 36, pp. 49–53, 2004.
-
Bednarik,
R., Moreno, A., Myller, N., Sutinen, E., Smart program visualization
technologies: Planning a next step, Proceedings of the 5th IEEE International
Conference on Advanced Learning Technologies (ICALT 2005), pp. 717-721, 2005.
-
Bruni
C., Ferrone C., Lucchetti M., A population set-based global optimization
procedure characterized by a births control strategy, Proc. of the IASTED
International Conference on Computational Intelligence, July 4-6, 2005 Calgary,
Alberta, Canada, pp. 298-303.
-
Cheung
R., An adaptive middleware infrastructure incorporating fuzzy logic for mobile
computing, Proc. International Conference on Next Generation Web Services
Practices (NWeSP 2005), 22-26 Aug. 2005, 3 pp. 449-451, 2005.
-
Delashmit
W.H. and Manry M.T., Recent developments in multilayer perceptron neural networks,
Proc. of the 7th Annual Memphis Area Engineering and Science Conference (MAESC
2005), May 2005, Memphis Tennessee USA, 2005.
-
Dukkipati
A., Murty M.N. and Bhatnagar S., Information theoretic justification of
Boltzmann selection and its generalization to Tsallis case, Proc. of the 2005
IEEE Congress on Evolutionary Computation, 2-5 Sept. 2005. vol. 2, pp.
1667-1674.
-
Enquist,
H.; Magnusson, J.; Nilsson, A., Change management implications for network
organizations, Proceedings of the 37th Hawaii Annual International Conference
on System Sciences, 5-8 Jan. 2004, pp.10.
-
Gouli
E., Gogoulou A., Papanikolaou K. and Grigoriadou M., Evaluating learner's
knowledge level on concept mapping tasks, Proc. 5th IEEE International
Conference on Advanced Learning Technologies (ICALT 2005), 5-8 July 2005, pp.
424-428.
-
Jansen,
B., Nakayama, K., Neural Networks Following a Binary Approach Applied to the
Integer Prime-Factorization Problem, Proc. IEEE International Joint Conference
on Neural Networks, Montreal, Canada, vol. 4, 31 July-4 Aug, 2005, pp.
2577-2582.
-
Kodogiannis
V.S. and Boulougoura M., Neural network-based approach for the classification
of wireless–capsule endoscopic images, Proc. of the International Joint
Conference on Neural Networks (IJCNN 2005), July 31–August 4, 2005, Montreal,
Quebec, Canada, vol. 4, pp. 2423–2428, 2005.
-
Kodogiannis
V.S., Boulougoura M. and Wadge E., Intelligent systems for the diagnosis of
wireless–capsule endoscopic images, Proc. of the 5th WSEAS Int. Conf. on
SIGNAL, SPEECH and IMAGE PROCESSING, Corfu, Greece, August, 17-19, pp259-264,
2005.
-
Li
J. and Duckett T., Three practical aspects on incremental training of RBF
network for robot behavior learning, Proc. of the SAIS–SSLS 2005, 3rd Joint
Workshop of the Swedish AI and Learning Systems Societies, Malardalen Sweden
April 12–14, 2005.
-
Pereira,
A., Fernandes, E.M., A New Algorithm for Identifying All Global Maxima Based on
Simulated Annealing, 6th World Congress on Structural and Multidisciplinary
Optimization, No .4991 May 30–June 3, 2005, Rio de Janeiro, Brazil, 2005.
-
Jin,
Y.-X., Cheng, H.-Z., Yan, J.-Y., Zhang, L., Local Optimum Embranchment Based
Convergence Guarantee Particle Swarm Optimization and its Application in
Transmission Network Planning, Proc. 2005 IEEE/PES Transmission and Distribution
Conference and Exhibition: Asia and Pacific, 15-18 Aug. 2005, Dalian, China,
pp. 1-6.
-
Engelbrecht,
A.P., Masiye, B.S., Pampara, G., Niching Ability of Basic Particle Swarm
Optimization Algorithms, Proc. IEEE 2005 Swarm Intelligence Symposium (SIS
2005), Pasadena, California, U.S.A., pp. 397-400, 2005
-
Encheva
S., Tumin S., Cooperative learning objects in an intelligent Web-based tutoring
system, Proc. of Advanced Industrial Conference on Telecommunications/Service
Assurance with Partial and Intermittent Resources Conference
(Telecommunications 2005), E-Learning on Telecommunications Workshop
(AICT/SAPIR/ELETE 2005), 17-20 July 2005, pp. 504-508, IEEE Press.
-
Liberal
F., Ferro A. and Fajardo J.O., Application of a PQoS Based Quality Management Model
to Identify Relative Importance of the Agents, the 5th International Conference
on Information, Communications and Signal Processing, 06-09 Dec. 2005, pp.
239-243.
-
Liberal
F., Ferro A., Jodra J.L., and Fajardo J.O, Application of General Perception-Based
QoS Model to Find Providers’ Responsibilities. Case Study: User Perceived Web
Service Performance, Proc of the Joint International Conference on Autonomic
and Autonomous Systems and International Conference on Networking and Services
(ICAS-ICNS 2005), 23-28 Oct. 2005, pp. 62-62.
-
Liu,
H., Chen, X., Chen, Y., Wavelet transform analyzing and real-time learning
method for myoelectric signal in motion discrimination, Proc. First
International Conference on Neural Interface and Control, pp. 127-130, 2005.
-
Schoeman,
L., Engelbrecht, A.P., Containing Particles Inside Niches when Optimizing
Multimodal Functions, Proc. 2005 Annual Research Conference of the South
African Institute of Computer Scientists and Information Technologists on IT
Research in Developing Countries (SAICSIT 2005), White River, South Africa, ACM
International Conference Proceeding Series; Vol. 150, 78-85, 2005.
-
Plagianakos
V .P .,Tasoulis D .K .and Vrahatis M .N .,Computational intelligence techniques
for acute leukemia gene expression data classification, Proc. of the
International Joint Conference on “Neural Networks ”,(IJCNN 2005)July 31
–August 4,2005,Montreal Quebec Canada, vol. 4, pp .2469–2474 [IEEE Catalog
Number :05 CH 37662 C ] [ISBN :0-7803-9049-0 ].
-
Rumetshofer
H. and Woss W., Semantic maps and meta-data enhancing e-accessibility in
tourism information systems, Proc. 16th International Workshop on Database and
Expert Systems Applications, 22-26 Aug. 2005, pp. 881-885
-
Jun,
L. and Duckett, T. Three practical aspects on incremental training of RBF
network for robot behaviour learning, Proc. SAIS-SSLS 2005, 3rd Joint Workshop
of the Swedish AI and Learning Systems Societies, 12–14 April, Malardalen,
Sweden, 2005.
-
Pavlidis
N.G., Tasoulis D.K., Plagianakos V.P., Nikiforidis G. and Vrahatis M.N.,
Spiking neural network training using evolutionary algorithms, Proc of the
International Joint Conference on Neural Networks (IJCNN2005), July 31–August
4, 2005, Montreal, Quebec, Canada, vol. 4, pp.2190–2194 [IEEE CatalogNumber:
05CH37662C] [ISBN: 0-7803-9049-0].
-
Pavlidis,
N.G., Tasoulis, D.K., Vrahatis, M.N., Time series forecasting methodology for
multiple-step-ahead prediction, Proceedings of the IASTED International
Conference on Computational Intelligence, pp. 456-461, 2005.
-
Sonntag
M. and Putzinger A., Interest derivation through keywords, Proc. of the 31st
EUROMICRO Conference on Software Engineering and Advanced Applications, 30
Aug.-3 Sept. 2005, pp. 475-482.
-
Tar,
J.K., Bencsik, A.L., Fractional order adaptive control for hydraulic differential
cylinders, Proceedings 3rd IEEE International Conference on Computational
Cybernetics (ICCC 2005), pp. 225-229, 2005.
-
Tasoulis
D.K., Plagianakos V.P. and Vrahatis M.N., Clustering in Evolutionary Algorithms
to Efficiently Compute Simultaneously Local and Global Minima, Congress on
Evolutionary Computation (CEC 2005), vol. 2, pp. 847-1854, 2005.
-
Wang
Z.Y., Guo C.X. and Cao Y.J., A new method for short-term load forecasting
integrating fuzzy-rough sets with artificial neural network, Proc. of the 7th
International Power Engineering Conference (IPEC 2005), 29 Nov.-2 Dec. 2005,
pp. 173-178.
-
Yu,
C., Manry, M.T., Narasimha, P.L., Sensitivity of nonlinear network training to
affine transformed inputs, Proceedings of the Eighteenth International Florida
Artificial Intelligence Research Society Conference, FLAIRS 2005 - Recent
Advances in Artifical Intelligence, pp. 591-596, 2005.
-
Zarraonandia
T., Fernandez C., Diaz P. and Torres J., On the way of an ideal learning system
adaptive to the learner and her context, Proc. 5th IEEE International
Conference on Advanced Learning Technologies (ICALT 2005), 5-8 July 2005, pp.
641-643.
-
Assis
A., Danchak M. and Polhemus L., Optimizing Instruction Using Adaptive
Hypermedia, Proc. 6th International Conference on Advanced Learning
Technologies, 05-07 July 2006, pp. 779-783.
-
Iivari
J., Iivari N., Varieties of User-Centeredness, Proc. of the 39th Annual Hawaii
International Conference on System Sciences (HICSS '06), 04-07 Jan. 2006, vol.
8, 176a-176a.
-
Iwamatsu,
M., Locating all the global minima using multi-species particle swarm
optimizer: The inertia weight and the constriction factor variants, Proc. IEEE
Congress on Evolutionary Computation (CEC 2006), pp. 816-822, 2006.
-
Kwok,
N.M., Liu, D.K., Tan, K.C., Ha, Q.P., An Empirical Study on the Settings of
Control Coefficients in Particle Swarm Optimization, Proc. IEEE 2006 Congress
on Evolutionary Computation (CEC 2006), 16-21 July 2006, pp. 823-830, 2006.
-
Menser,
S., Hereford, J., A New Optimization Technique, Proc. IEEE SoutheastCon, March
31- April 2, Memphis (TN), U.S.A., pp. 250-255, 2006.
-
Ben
Niu, Yunlong Zhu, Xiaoxian He, Xiangping Zeng, An Improved Particle Swarm
Optimization Based on Bacterial Chemotaxis, Proc. of the 6th World Congress on
Intelligent Control and Automation (WCICA 2006), 21-23 June 2006, vol. 1, pp.
3193-3197.
-
Brkovic
M., Milosevic D., and Krneta R., SCos for adaptive E-learning, Proc. 28th
International Conference on Information Technology Interfaces, June 19-22,
2006, pp. 29-34.
-
Gongora
M. and Ashfaq W. Analysis of Passenger Movement at Birmingham International
Airport using Evolutionary Techniques, Proc. IEEE Congress on Evolutionary
Computation (CEC 2006), 16-21 July 2006, pp. 1339-1345.
-
Grigoriadou
M., Gouli E., Gogoulou A. and Samarakou M., Serving Learning and Assessment in
SCALE, Proc. 6th International Conference on Advanced Learning Technologies,
05-07 July 2006, pp. 886-890.
-
O'Hora
B., Perera J. and Brabazon A., Designing Radial Basis Function Networks for
Classification Using Differential Evolution, Proc. International Joint
Conference on Neural Networks (IJCNN '06), 16-21 July 2006, pp. 2932-2937.
-
He,
Y.-C., Liu, K.-Q., A modified particle swarm optimization for solving global
optimization problems, Proceedings of the Fifth International Conference on
Machine Learning and Cybernetics, (ICMLC 2006), August 13-16, 2006, Dalian,
China, art. no. 4028423, pp. 2173-2177, IEEE 2006.
-
Masun
H., Rania L. and Ghias B., Adaptive Web-Based Educational System using Neural
Networks in EFL Course, Proc. of the 2nd Conference Information and
Communication Technologies (ICTTA '06), 24-28 April 2006, vol. 1, pp. 622-625.
-
Zielinski
K., Laur R., Constrained Single-Objective Optimization Using Particle Swarm
Optimization, Proc. IEEE 2006 Congress on Evolutionary Computation (CEC 2006),
16-21 July 2006, pp. 443-450, 2006.
-
Vilarino
F., Spyridonous P., Vitria J., Azpiroz F. and Radeva P., Cascade analysis for
intestinal contraction detection, Proc. of the Computer Assisted Radiology and
Surgery (CARS 2006), June 28-July 1, 2006, Osaka, Japan, pp.9-12, 2006.
-
Sans
V., Sequence mining over ARM Hypermedia presentations, Proc. 2nd Conference
Information and Communication Technologies (ICTTA '06), 24-28 April 2006, vol.
1, pp. 552-557.
-
Vilarino
F., Spyridonos P., Vitria J., Azpiroz F., Radeva P., Automatic Detection of
Intestinal Juices in Wireless Capsule Video Endoscopy, 18th International
Conference on Pattern Recognition, (ICPR 2006), August 20-24, 2006, Hong Kong,
China, vol. 4, pp. 719-722.
-
Kranzusch
K., Abort determination with non-adaptive neural networks for the mars
precision landers, Proc. 44th AIAA Aerospace Sciences Meeting and Exhibit;
Reno, NV; USA; 9-12 Jan. 2006. pp. 1-11. 2006.
-
Papaioannou,
I.V.; Roussaki, I.G.; Anagnostou, M.E., Towards successful automated
negotiations based on Neural Networks, Proc. of the 5th IEEE/ACIS International
Conference on Computer and Information Science and 1st IEEE/ACIS International
Workshop on Component-Based Software Engineering, Software Architecture and
Reuse (ICIS-COMSAR 2006) July 10-12, 2006, Honolulu, Hawaii, USA, pp.464-472,
2006.
-
Passaro
A. and Starita A., Clustering particles for multimodal function optimization,
In: Proceedings of the
-
ECAI
Workshop on Evolutionary Computation, August 28, 2006, Riva del Garda, Italy,
pp.51-55, 2006.
-
Ruan,
X., Liu, L., Yu, N., Ding, M., A model of feedback error learning based on
Kalman estimator, Proceedings of the World Congress on Intelligent Control and
Automation (WCICA), 1, pp. 4190-4194, 2006.
-
Sevarac
Z., Neuro Fuzzy Reasoner for Student Modeling, Proc. 6th International
Conference on Advanced Learning Technologies, 05-07 July 2006, pp. 740-744.
-
Vert,
G.; Yakkali, R., Towards A Collaborative Model Of An Automated Adaptive Content
Delivery Training Utilizing Fuzzy Logic Proc. International Symposium on
Collaborative Technologies and Systems (CTS 2006), 14-17 May 2006, pp. 165-171.
-
Wissner-Gross
A.D., Preparation of Topical Reading Lists from the Link Structure of
Wikipedia, Proc. 6th International Conference on Advanced Learning
Technologies, 05-07 July 2006, pp. 825-829.
-
Yecan
E. and Calgiltay K., Cognitive Styles and Students’ Interaction with an
Instructional Web-site: Tracing Users through Eye-gaze, Proc. 6th International
Conference on Advanced Learning Technologies, 5-7 July 2006, pp. 340-342.
-
Yu
Cao, Danyu Liu, Wallapak Tavanapong, Johnny Wong, JungHwan Oh, and Piet C. de
Groen, Automatic Classification of Images with Appendiceal Orifice in
Colonoscopy Videos, In: 28th IEEE 2006 International Conference of the
Engineering in Medicine and Biology Society (EMBS 2006), Engineering Revolution
in BioMedicine, Aug 30-Sept. 3, 2006, New York City, New York, USA, 2006.
-
Guiling
Zhang and Jizhou Sun, Grid intrusion detection based on soft computing by
modeling real-user's normal behaviors, Proc. IEEE International Conference on
Granular Computing, 10-12 May 2006, pp. 558-561.
-
Roussaki,
I., Papaioannou, I., Anagnostou, M., Employing neural networks to assist
negotiating intelligent agents, Proceedings of the 2nd Institution of
Engineering and Technology International Conference on Intelligent
Environments, IET Conference Publications, Issue 518, Athens, Greece, 5-6 July
2006 , ISBN: 0 86341 663 2, vol. 1, 101-110, 2006.
-
Wang
Zhiyong and Cao Yijia, Mutual Information and Non-fixed ANNs for Daily Peak
Load Forecasting, Power System Conference and Exposition (PSCE 2006), pp.
1523-1527, 2006.
-
Bommanna
Raja K., Madheswaran M.and Thyagarajah K., Analysis of Ultrasound kidney Images
using Content Descriptive Multiple Features for Disorder Identification and ANN
based Classification, Proceedings of the International Conference on Computing:
Theory and Applications (ICCTA'07).
-
Castellano,
M.; Mastronardi, G.; Di Giuseppe, G.; Dicensi, V., Neural Techniques to Improve
the Formative Evaluation Procedure in Intelligent Tutoring Systems, IEEE
International Conference on Computational Intelligence for Measurement Systems
and Applications (CIMSA 2007), 27-29 June 2007, pp. 63-67.
-
Garcia-Valdez,
M.; Castillo, O.; Licea, G.; Alanis, A., Simple Sequencing and Selection of
Learning Objects using Fuzzy Inference, Proceedings of the Annual Meeting of
the North American Fuzzy Information Processing Society (NAFIPS '07), 24-27
June 2007, pp. 628-632.
-
Yi-Chao
He; Kun-Qi Liu; A Modified Particle Swarm Optimization for Solving Global
Optimization Problems, Proceedings of the International Conference on Machine
Learning and Cybernetics, Aug. 2006, pp. 2173-2177.
-
Kahraman,
Hamdi Tolga; Colak, Ilhami; Sagiroglu, Seref, A Web Based Adaptive Educational
System, Proceedigns of the 6th International Conference on Machine Learning and
Applications (ICMLA 2007), 13-15 Dec. 2007, pp.286-291.
-
Takeshi
Korenaga, Toshiharu Hatanaka and Katsuji Uosaki, Performance Improvement of
Particle Swarm Optimization for High-Dimensional Function Optimization, 2007
IEEE Congress on Evolutionary Computation (CEC 2007), 3288-3293.
-
Liu,
Z., Elhanany, I., A scalable model-free recurrent neural network framework for
solving POMDPs, Proceedings of the 2007 IEEE Symposium on Approximate Dynamic
Programming and Reinforcement Learning (ADPRL 2007), pp. 119-126, 2007.
-
Nicolau
Jr., D.V., Nicolau, D.V., Maini, P.K., A biomimetic algorithm for the improved
detection of microarray features, Progress in Biomedical Optics and Imaging - Proceedings
of SPIE, 6441, art. no. 64411C, 2007.
-
Popescu,
E.; Trigano, P.; Badica, C., Adaptive Educational Hypermedia Systems: A Focus
on Learning Styles, Proceedings of EUROCON 2007: The International Conference
on "Computer as a Tool", 9-12 Sept. 2007 pp.2473-2478.
-
Wang,
H., Li, C., Liu, Y., Zeng, S., A hybrid particle swarm algorithm with cauchy
mutation, Proceedings of the 2007 IEEE Swarm Intelligence Symposium (SIS 2007),
pp. 356-360, 2007.
-
Yu-Xuan
Wang, Zhen-Dong Zhao and Ran Ren, Hybrid Particle Swarm Optimizer with Tabu
Strategy for Global Numerical Optimization, 2007 IEEE Congress on Evolutionary
Computation (CEC 2007), 2310-2316.
-
Zhenzhen
Liu,Itamar Elhanany, Fast and Scalable Recurrent Neural Network Learning based
on Stochastic Meta-Descent, Proceedings of the 2007 American Control
Conference, Marriott Marquis Hotel at Times Square, New York City, USA, July
11-13, 2007, pp 5694-5699.
Home - Teaching - Publications - Bio - Blog - Department
In
electronic resources and technical reports
-
Grossenbacher
F .and Ludwig Ch .A .,Magazine review “Medicine
Computer Science” of the Swiss Society for Medical Informatics, “SGMI /SSIM
-Zeitschriftenreview ‘Medizinische Informatik ’”, 2000.
-
Iplikci
S ., An Improved Algorithm for Convergence in Training Feedforward Neural
Networks, IEEE NNC SRG 2000 -Final
Report .Available on -line at:
ewh.ieee.org/tc/nnc/edu/research/reports-2000/iplikci2000.pdf
-
Karkkainnen
T .,MLP-Network in a Layer -Wise Form :Derivations Consequences and
Applications to weight Decay, Reports of the Department of Mathematical
Information Technology Series C Software Engineering and Computational
Intelligence No .C 1/2000,University of Jyvaskyla Finland.
-
Kestler
H .A .,Schwenker F .and Palm G .,RBF network classification of ECGs as a
potential marker for sudden cardiac death Ulmer Informatik -Berichte 2001-03,
University of Ulm Germany 2001 [ISSN 0939-5091 ]. Available on-line at:
http://vts.uni-ulm.de/docs/2005/5352/vts_5352.pdf
-
Lampinen
J., A bibliography of differential evolution algorithm, Technical Report,
Lappeenranta University of Technology Department of Information Technology
Laboratory of Information Processing Finland. Available on-line at:
http://www2.lut.fi/~jlampine/debiblio.htm Updated 12/01/2002.
-
Binos
T .,Evolving neural network architecture and weights using an evolutionary
algorithm, Master Thesis of Applied Science in Information Technology,
Department of Computer Science, RMIT University, Melbourne Australia, April 10,
2003.
-
Al-Tayeche
R .and Khalil A .,CBIR :Content based image retrieval
Final Report Department of Systems and Computer Engineering Faculty of
Engineering Carleton University Ottawa Ontario Canada April 4,2003. Available
Available on-line at:
http://www.sce.carleton.ca/faculty/cuhadar/CBIR/files/finalreport.doc
-
Niemann
H., Klassifikation von Mustern. überarbeitete Auflage
in the Internet, 2003. [Updated version
of the book “Pattern Analysis and Understanding”, second edition. Springer Series
in Information Sciences 4. Springer, Berlin Heidelberg 1990].
-
van der Vlerk M.H., Stochastic Programming
Bibliography. Available online at: http://mally.eco.rug.nl/spbib.html,
1996-2003.
-
Satya
N.V.A., Protein secondary structure prediction from amino acid sequences using
a neural network classifier based on the Dempster -Shafer theory, Thesis for
the degree of Master of Science (Computer Science ), Faculty of Computer
Science and Information Systems Universiti Teknologi Malaysia, 2003. [http://web.sfc.keio.ac.jp/satya/2003.DBNNthesis.pdf]
-
Brautigam
N., Training Neuronaler Netze mit Methoden der mathematischen Optimierung,
Diplomarbeit zur Erlangung des akademischen Grades Diplom-Mathematiker,
Friedrich-Schiller-Universitat Jena, Institut fur Angewandte Mathematik,
Fakultat fur Mathematik und Informatik Jena, Germany, January 12, 2004.
-
Neumaier
A., Online papers in global optimization, 2004. Available on-line at : http://
http://www.mat.univie.ac.at/~neum/glopt/mss/gloptpapers.html
-
Tino
P., Introduction to neural computation:Course material
and useful links, MSc in Advanced Computer Science/Natural Computation, School
of Computer Science, The University of Birmingham, Edgbaston UK, October
4,2004. Available on-line at: http://www.cs.bham.ac.uk/~pxt/inc.html
-
Wickstrom
A. and Svensson O., Neural modelling of the offset printing process, Computer
Systems Engineering and Electrical Engineering (IDE 0416), School of
Information Science, Computer and Electrical Engineering, Halmstad University,
Sweden, March 30, 2004. Available on-line at: www.t2f.nu/t2frapp_f_109.pdf
-
Bex
P., Implementing a process scheduler using neural network technology, Nijmeegs
Instituut voor Cognitie en Informatie, Radboud University, Nijmegen Nijmegen,
The Netherlands 2005.
-
Campana,
E.F., Fasano, G., Pinto, A., Particle Swarm Optimization: Dynamic System
Analysis for Parameter Selection in Global Optimization Frameworks, Technical
Report INSEAN 2005-023, Instituto Nazionale per Studi ed Esperienze di
Architettura Navale INSEAN, Italy.
-
Sammer
L., Merkmalbasierte Zeichenerkennung mittels neuronaler Netze (Character
recognition by means of neural nets), University of Bayreuth, Mathematisches
Institut, 2005.
[http://www.uni-bayreuth.de/departments/math/~lgruene/diplom/lisa_sammer_diplom
.pdf]
-
Schutte
J.F., The particle swarm optimization algorithm, Structural Optimization
Graduate course in the area of Structures and Optimization, Department of
Aerospace Engineering Mechanics and Engineering Science, University of Florida
USA , 2005. Available on-line at:
http://www.mae.ufl.edu/haftka/stropt/Lectures/PSO_introduction.pdf
-
Vaz,
A.I.F., Vicente, L.N., A Particle Swarm Pattern Search Method for Bound
Constrained Nonlinear Optimization, Technical Report 06-08, Department of
Mathematics, University of Coimbra, Portugal, 2006.
-
Redi
J., Tecniche di computational intelligence per la fattorizzazione di numeri
grandi, Tesi di laurea magistrale, Corso di Laurea in Ingegneria Elettronica,
Dipartimento di Ingegneria Biofisica ed Elettronica,
Facolta di Ingegneria, Universita degli Studi di Genova, Genova, Italia, 24
Luglio 2006.
-
Hu
X., A bibliography of Particle Swarm Optimization, available online at
http://www.swarmintelligence.org/bibliography.php (last accessed 17/11/2006).
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