Structure/Parameter Optimization of Fuzzy Models by Evolutionary Algorithm

M.-S. Kim, C.-H. Kim, and J.-J. Lee (Korea)


Evolutionary algorithm, Fuzzy modeling


In this paper, a new evolutionary algorithm for designing fuzzy models will be proposed. The structure and parame ters of fuzzy models are simultaneously optimized by the proposed evolutionary algorithm. The objectives are in twofold. On the one hand, we are try to develop a fast and practical method for modeling high dimensional com plex systems with a as possibly simplified fuzzy model. On the other hand, we hope that the resulting fuzzy model is easy to understand, that is, the resulting fuzzy model do not lose its interpretability. Through simulations on model ing problems, it will be shown that the proposed algorithm can successfully find a fuzzy model which approximates the given unknown function accurately with compact num ber of rules.

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