Identification of Fuzzy Models Using Cartesian Genetic Programming

Fuzzy models have capability for solving problem in different application such as pattern recognition, prediction and control. Nevertheless, it has to be emphasized that the identification of a fuzzy model is complex task with many local minima. Cartesian genetic programming provides a way to solve such complex optimization problem. In this paper, fuzzy model is in form of network. Cartesian genetic programming is used to optimize the antecedent part and recursive least square is used to optimized the consequent part. The initialization of membership function parameters are doing with fuzzy clustering. Benefit of the methodology is illustrated by simulation results.