A Modified Genetic Algorithm for Training Adaptive Fuzzy Systems

Abstract

Adaptive Fuzzy Logic Systems trained by genetic evolution of their parameters are presented in this work. This technique is based on the aggregation of parameter perturbations. Neither the evaluation function nor the membership functions, have to be differentiable as required in most optimization techniques. In the classical Genetic Algorithms, the solution… (More)
DOI: 10.1080/10798587.2008.10643005

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