Optimization of fuzzy expert systems using genetic algorithms and neural networks
Christiaan Perneel, J.-M. Themlin, Jean-Michel Renders, Marc P. J. Acheroy · IEEE Transactions on Fuzzy Systems · 1995
In this paper, fuzzy logic theory is used to build a specific decision-making system for heuristic search algorithms. Such algorithms are 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 techniques based on a neural network formulation of the problem, are used to obtain an improvement of the performance. The decision-making system and both optimization methods are tested on a target recognition system.>