Determination of antecedent structure for fuzzy modeling using genetic algorithm

Fuzzy modeling is one of the promising methods for describing nonlinear systems. Determination of antecedent structures of fuzzy models, i.e. input variables and number of membership functions for the inputs has been one of the most important problems of the fuzzy modeling. This paper presents a new method to find proper structures in the antecedent for fuzzy modeling of nonlinear systems using genetic algorithm. The new method is effective to identify precise fuzzy models of systems with strong nonlinearities. A simulation is done to show the effectiveness of the proposed method