Structure optimization of fuzzy neural network as an expert system using genetic algorithms

Benyamin Kusumoputro; Ponix Irwanto

doi:10.1117/12.380573

30 March 2000 Structure optimization of fuzzy neural network as an expert system using genetic algorithms

Benyamin Kusumoputro, Ponix Irwanto

Proceedings Volume 4055, Applications and Science of Computational Intelligence III; (2000) https://doi.org/10.1117/12.380573
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In this article we developed a method for optimizing the structure of a fuzzy artificial neural networks through genetic algorithms. This genetic algorithm is used by optimizing the number of weight connections in a neural network structure, by the evolution of those structures as individuals in a population. It is found that the optimization of the neural network provides higher confidence accuracy of the suggested solution in a case based diagnostic system. The computational cost of the optimized network also improved considerably high.

Citation Download Citation

Benyamin Kusumoputro and Ponix Irwanto "Structure optimization of fuzzy neural network as an expert system using genetic algorithms", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); https://doi.org/10.1117/12.380573

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