<title>Structure optimization of fuzzy neural network as an expert system using genetic algorithms</title>

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.