An evolutionary clustering technique with local search to design RBF neural network classifiers

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 3, Issue , 2004, Pages 2083-2088

  De Castro, Leandro N ^a   Hruschka, Eduardo R ^a   Campello, Ricardo J G B ^a  

^a CATHOLIC UNIVERSITY OF SANTOS   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; GENETIC ALGORITHMS; MATHEMATICAL TRANSFORMATIONS; MATRIX ALGEBRA; PROBLEM SOLVING; VECTORS;

CLUSTERING GENETIC ALGORITHM (CGA); EVOLUTIONARY CLUSTERING; LOCAL SEARCH; NONLINEAR TRANSFORMATION;

RADIAL BASIS FUNCTION NETWORKS;

EID: 10844247179     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. L. Yingwei, N. Sundararajan, and P. Saratchandran, "A sequential learning scheme for function approximation using minimum radial basis function neural networks", Neural Computation, vol. 9, no. 9, pp. 461-478, 1997.
2. Y.-S. Hwang and S.-Y. Bang, "An Efficient Method to Construct Radial Basis Function Neural Network Classifier", Neural Networks, vol. 10, no. 8, pp. 1495-1503, 1997.
3. B. A. Whitehead and T. D. Choate, "Cooperative-Competitive Genetic Evolution of Radial Basis Function Centers and Widths for Time Series Prediction", IEEE Trans. on Neural Networks, vol. 7, no. 4, pp. 869-880, 1996.
4. J. Park and I. W. Sandberg, "Universal Approximation Using Radial Basis Function Networks", Neural Computation, vol. 3, n. 2, pp. 246-257, 1991.
5. T. Poggio and F. Girosi, "Networks for Approximation and Learning", Proceedings of the IEEE, vol. 78, no. 9, pp. 1481-1497, 1990.
6. M. J. L. Orr, "Regularisation in the Selection of Radial Basis Function Centres", Neural Computation, vol. 7, no. 3, pp. 606-623, 1995.
7. C. Panchapakesan, M. Palaniswami, D. Ralph, and C. Manzie, "Effects of Moving the Centers in an RBF Network", IEEE Trans. on Neural Networks, vol. 13, no. 6, pp. 1299-1307, 2002.
8. M. J. D. Powell, "Radial Basis Function Approximations to Polynomials", Numerical Analysis 1987 Proceedings, pp. 223-241, Dundee, UK.
9. D. S. Broomhead and D. Lowe, "Multivariable Functional Interpolation and Adaptive Networks", Complex Systems, vol. 2, pp. 321-355, 1988.
10. R. P. Lippmann, "Pattern Classification Using Neural Networks", IEEE Communications Magazine, vol. 27, no. 11, pp. 47-63, 1989.
11. A. Jayasuria and S. K. Halgamuge, "An Enhanced Clustering Method for Multiple Shape Basis Function Networks", In Proc. of the IEEE Int. Joint Conf. on Neural Networks, pp. 7-11, 1998.
12. E. L. Sutanto, J. D. Mason and K. Warwick, "Mean-Tracking Clustering Algorithm for Radial Basis Function Centre Selection", Int. J. Control, vol. 67, no. 6, pp. 961-977, 1997.
13. N. B. Karayiannis and G. W. Mi, "Growing Radial Basis Neural Networks: Merging Supervised and Unsupervised Learning with net-work Growth Techniques", IEEE Trans. on Neural Networks, vol. 8, no. 6, pp. 1492-1506, 1997.
14. B. Fritzke, "Fast Learning with Incremental RBF Networks", Neural Processing Letters, vol. 1, no. 1, pp. 2-5, 1994.
15. D. Wettschereck and T. G. Dietterich, "Improving the Performance of Radial Basis Function Networks by Learning Center Locations", In J. E. Moody, S. J. Hanson and R. P. Lippmann, editors, Advances in Neural Information Processing Systems, 4, pp. 1133-1140, Morgan Kaufmann, San Francisco, CA, 1992.
16. L. Yingwei, N. Sundararajan and P. Saratchandran, "A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks", Neural Computation, vol. 9, no. 9, pp. 461-478, 1997.
17. B. Burdsall and C. Giraud-Carrier, "GA-RBF: A Self-Optimising RBF Network", In Proc. of the Third International Conference on Artificial Neural Networks and Genetic Algorithms, Norwich, U.K., pp. 346-349, 1997.
18. E. G. M. Lacerda, A. C. P. L. F. de Carvalho and T. B. Ludermir, "Evolutionary Optimization of RBF Networks", Int. J. of Neural Systems, vol. 11, no. 3, pp. 287-294, 2001.
19. D. H. Wolpert and W. G. Macready, "No Free Lunch Theorems for Optimization", IEEE Trans. on Evolutionary Computation, vol. 1, no. 1, pp. 67-82, 1997.
20. E. R. Hruschka, N. F. F. Ebecken, "A genetic algorithm for cluster analysis", Intelligent Data Analysis, v. 7(1), pp. 15-25, IOS Press, Netherlands, 2003.
21. L. Kaufman, P. J. Rousseeuw, "Finding Groups in Data - An Introduction to Cluster Analysis", Wiley Series in Probability and Mathematical Statistics, 1990.
22. S. A. Billings and G. L. Zheng, "Radial Basis Function Network Configuration Using Genetic Algorithms", Neural Networks, vol. 8, no. 6, pp. 877-890, 1995.
23. S. Chen, Y. Wu, B. L. Luk, "Combined Genetic Algorithm Optimization and Regularized Orthogonal Least Squares Learning for Radial Basis Function Neural Networks", IEEE Trans. on Neural Networks, vol. 10, no. 5, pp. 1239-1243.
24. C. A. Micchelli, "Interpolation of Scattered Data: Distance Matrices and Conditionally Positive Definite Functions", Construct. Approx., vol. 2, pp. 11-22, 1986.
25. S. Chen, E. S. Chng and K. Alkadhimi, "Regularized Orthogonal Least Squares Algorithm for Constructing Radial Basis Function Networks", Int. Journal of Control, vol. 64, no. 5, pp. 829-837, 1996.
26. J. A. S. Freeman and D. Saad, "Learning and Generalization in Radial Basis Function Networks", Neural Computation, vol. 7, no. 5, pp. 1000-1020, 1995.
27. nd Ed., 1999.
28. L. N. de Castro and F. J. Von Zuben, "An Improving Pruning Technique with Restart for the Kohonen Self-Organizing Feature Map", In Proc. of IJCNN, Washington D.C., vol. 3, pp. 1916-1919, 1999.
29. L. N. de Castro and F. J. Von Zuben, "Automatic Determination of Radial Basis Functions: An Immunity-Based Approach", Int. J. of Neural Systems, vol. 11, no. 6, pp. 523-535, 2001.
30. R. A. Fisher, "The Use of Multiple Measurements in Taxonomic Problems", Ann. Eugenics, vol. 7, no. 2, pp. 179-188, 1936.
31. R. P. Gorman and T. J. Sejnowski, "Analysis of Hidden Units in a Layered Network Trained to Classify Sonar Targets", Neural Networks, vol. 1, no. 1, pp. 75-89, 1988.
32. S. Cohen and N. Intrator, "A Hybrid Projection Based and Radial Basis Function Architecture", In J. Kittler and F. Roli, editors, Proc. Int. Workshop on Multiple Classifier Systems, Lecture Notes in Computer Science 1857, pp. 147-156, Sardingia, Springer, 2000.
33. M. R. Berthold and J. Diamond, "Boosting the Performance of RBF Networks with Dynamic Decay Adjustment", In G. Tesauro, D. S. Touretzky, and T. K. Leen, editors, Advances in Neural Information Processing Systems, v. 7, pp. 521-528, Cambridge, MIT Press, 1995.