A Novel Hybrid Optimization Method with Application in Cascade-Correlation Neural Network Training

In this paper, based on the fusion of the clonal selection algorithm (CSA) and differential evolution (DE) method, we propose a novel optimization scheme: CSA-DE. The DE is employed here to increase the affinities of the clones of the antibodies (Abs) in the CSA. Several nonlinear functions are used to verify and demonstrate the effectiveness of this hybrid optimization approach. It is further applied for the construction of the cascade-correlation (C-C) neural network, in which the optimal hidden nodes can be obtained.

[1]  P. Hajela,et al.  Immune network simulations in multicriterion design , 1999 .

[2]  Xiaolei Wang,et al.  A novel particle swarm-based method for nonlinear function optimization , 2008 .

[3]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[4]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[5]  K. Lang,et al.  Learning to tell two spirals apart , 1988 .

[6]  G L Ada,et al.  The clonal-selection theory. , 1987, Scientific American.

[7]  F. Azuaje.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[8]  Riccardo Poli,et al.  Foundations of Genetic Programming , 1999, Springer Berlin Heidelberg.

[9]  D. Dasgupta,et al.  Advances in artificial immune systems , 2006, IEEE Computational Intelligence Magazine.

[10]  S.J. Ovaska,et al.  A hybrid optimization algorithm in power filter design , 2005, 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005..

[11]  Hisao Ishibuchi,et al.  Hybrid Evolutionary Algorithms , 2007 .

[12]  Xiao Zhi Gao,et al.  Artificial immune optimization methods and applications - a survey , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[13]  Xiao Zhi Gao,et al.  A Hybrid Optimization Algorithm Based on Ant Colony and Immune Principles , 2007, Int. J. Comput. Sci. Appl..

[14]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[15]  Christian Lebiere,et al.  The Cascade-Correlation Learning Architecture , 1989, NIPS.

[16]  Martin Middendorf,et al.  A hierarchical particle swarm optimizer and its adaptive variant , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).