New Genetic Algorithm for Neural Network Structure Optimization

L. Körösi(1*), Š. Kozák(2)

(1) Slovak University of Technology in Bratislava, Slovakia
(2) Slovak University of Technology in Bratislava, Slovakia
(*) Corresponding author


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Abstract


One of the very important tasks in modeling and control nonlinear processes is the determination of optimal artificial neural network (ANN) structure. Genetic algorithms (GA) are one of the many methods used for artificial neural networks structure optimization. Their disadvantage could be a long search time for finding of optimal solutions. This paper presents new algorithms based on genetic operations which enables to accelerate the optimization process using orthogonal activation function based neural networks (AOF NN).
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Keywords


Neural Network; Genetic Algorithm; Genetic Operation

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References


Depenau, J., Automated design of ANN architecture for classification, Ph.D. Thesis, Computer Science Department, Aarhus University, 1995.

Wahlberg, B., Orthonormal Basic Functions Models. A Transformation Analysis, IFAC 14th Triennial World Congress, Beijing, P. R. China, pp. 355-360, 1999.

Kvasnička, V. Beňušková, Ľ., Úvod do teórie neurónových sietí. (IRIS, Bratislava, 1997).

Holland, J., H., Adaptation in natural and Artificial Systems. An introductory analysis with applications to biology, control and artificial intelligence (Mit Press, 1992).

Bundzel, M., Neurónové siete s adaptívnou topológiou, (Katedra Kybernetiky a Umelej Inteligencie, Technická Univerzita Košice, 1999).

Körösi, L., Kozák, Š., Optimal Self Tuning Neural Network Controller Design. 16th IFAC world congress, Praha, Česká republika, 3.-8.7.2005.

Megherbi A. C., Megherbi H., Benmahamed K., Aissaoui A. G., Tahour A., Parameters Identification of a Nonlinear System Based on Genetic Algorithms with an Optimized Cost Function, (2008) International Review of Automatic Control (IREACO), 1 (1), pp. 15-18.

Talbi N., Belarbi K., Automatic Generation of Fuzzy Rule Base by a Hybrid Approach: Application to Control and Modeling, (2012) International Review of Automatic Control (IREACO), 5 (2), pp. 284-291.

Errachdi A., Saad I., Benrejeb M., On-line Identification Method Based on Dynamic Neural Network, (2010) International Review of Automatic Control (IREACO), 3 (5), pp. 474-479.


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