Multi-objective evolutionary optimization of neural networks for virtual reality visual data mining: Application to hydrochemistry

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn , Issue , 2007, Pages 2233-2238

  Valdés, Julio J ^a   Barton, Alan J ^a  

^a NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; DATA MINING; DECISION SUPPORT SYSTEMS; DIESEL ENGINES; GENETIC ALGORITHMS; INFORMATION MANAGEMENT; MINING; MULTIOBJECTIVE OPTIMIZATION; OPTIMIZATION; VIRTUAL REALITY; VISUAL COMMUNICATION;

NEURAL NETWORKS;

EID: 51749117376     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2007.4371305     Document Type: Conference Paper

References (28)

1. I. Borg and J. Lingoes, Multidimensional similarity structure analysis. Springer-Verlag, 1987.
2. E. K. Burke and G. Kendall, Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques. Springer Science and Business Media, Inc. New York, 2005.
3. J. L. Chandon and S. Pinson. Analyse typologique. Théorie et applications. Masson, Paris, 1981.
4. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multi-objective genetic algorithm: Nsga-ii," Technical Report 2000001, Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology Kanpur, 2000.
5. K. Deb, S. Agarwal, A. Pratap, and T. Meyarivan, "A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: Nsga-ii," Proceedings of the Parallel Problem Solving from Nature VI Conference, pp. 849-858, Paris, France, 16-20 September 2000.
6. K. Deb, S. Agarwal, and T. Meyarivan, "A fast and elitist multi-objective genetic algorithm: Nsga-ii," IEEE Transaction on Evolutionary Computation, vol. 6 (2), pp. 181-197, 2002.
7. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. Wiley New York, 1972.
8. Fagundo J.R., Valdés J. J., Pulina M. Hydrochemical Investigations in Extreme Climatic Areas, Cuba and Spitzbergen. Water Resources Management and Protection in Tropical Climates. pp 45-54 Stockholm, 1990.
9. Fagundo J.R., Valdés J. J., Rodríguez J.E. Karst Hydrochemistry (in Spanish). Research Group of Water Resources and Environmental Geology. University of Granada, Spain. Osuna, 1996.
10. K. Fukunaga, Introduction to Statistical Pattern Recognition. Academic Press, 1972.
11. J. C. Gower, "A general coefficient of similarity and some of its properties," Biometrics, vol.1 no.27, pp.857-871, 1971.
12. J. Hartigan, Clustering Algorithms. John Wiley & Sons, 1975.
13. A. K. Jain and J. Mao, "Artificial neural networks for nonlinear projection of multivariate data," 1992 IEEE joint Conf. on Neural Networks, pp. 335-340, Baltimore, MD, 1992.
14. M. Jianchang and A. Jain, "Artificial neural networks for feature extraction and multivariate data projection," IEEE Trans. On Neural Networks, vol. 6(2), pp.1-27, 1995.
15. J. Kruskal, "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psichometrika, vol. 29 pp.1-27, 1964.
16. J. Mao and A. K. Jain, "Discriminant analysis neural networks," 1993 IEEE International Conference on Neural Networks, pp. 300-305, San Francisco, California, March 1993.
17. J. Mao and A. K. Jain, "Artificial neural networks for feature extraction and multivariate data projection,"IEEE Trans. on Neural Networks, vol. 6 pp.296-317, 1995.
18. T. Masters. Advanced Algorithms for Neural Networks. John Wiley & Sons, 1993.
19. V. Pareto, Cours D'Economie Politique, volume I and II. F. Rouge, Lausanne, 1896.
20. Press, W.H., Flannery, B.P., Teukolsky, S.A. and Vetterling, W.T. Numerical Recipes in C, Cambridge University Press, New York, 1986.
21. J. W. Sammon, "A non-linear mapping for data structure analysis," IEEE Trans. Computers, C18 pp.401-408, 1969.
22. Valdés J. J., "Virtual reality representation of relational systems and decision rules," In P. Hajek, editor, Theory and Application of Relational Structures as Knowledge Instruments, Meeting of the COST Action 274. Prague, Nov 2002.
23. Valdés J. J., "Similarity-based heterogeneous neurons in the context of general observational models," Neural Network World, vol. 12(5) pp. 499-508, 2002.
24. J. J. Valdés, "Virtual reality representation of information systems and decision rules," Lecture Notes in Artificial Intelligence, vol. 2639 LNAI, pp. 615-618. Springer-Verlag, 2003.
25. J. Valdés, "Building virtual reality spaces for visual data mining with hybrid evolutionary-classical optimization: Application to microarray gene expression data," 2004 IASTED International Joint Conference on Artificial Intelligence and Soft Computing, ASC'2004, pp. 161-166, Marbella, Spain, Sept 2004. ACTA Press, Anaheim, USA.
26. J. J. Valdés, A.J. Barton, "Virtual Reality Visual Data Mining with Nonlinear Discriminant Neural Networks: Application to Leukemia and Alzheimer Gene Expression Data," Proceedings of the IJCNN'05 International Joint Conference on Neural Networks, Montreal, 2005.
27. A. R. Webb and D. Lowe, "The optimized internal representation of a multilayer classifier," Neural Networks, vol. 3, pp.367-375, 1990.
28. P. Walker, B. Smith, Y. Qing, F. Famili, J. J. Valdés, L. Ziying, and L. Boleslaw, "Data mining of gene expression changes in alzheimer brain," Artificial Intelligence in Medicine, vol. 31, pp.137-154, 2004.