OPTIMIZATION OF FUZZY EXPERT-SYSTEMS USING GENETIC ALGORITHMS AND NEURAL NETWORKS

In this paper, the fuzzy logic theory is used to build a specific deci sion-making system for heuristic search algorithms. Such algorithms ar e typically used for expert systems. To improve the performance of the overall system, a set of important parameters of the decision-making system is identified. Two optimization methods for the learning of the optimum parameters, namely genetic algorithms and gradient-descent te chniques based on a neural network formulation of the problem, are use d to obtain an improvement of the performance. The decision-making sys tem and both optimization methods are tested on a target recognition s ystem.