Industrial Automatic Control Systems and Controllers Annotation << Back The Mechanism of Adaptation Fuzzy Inference System Based on Genetic Algorithm M.V. Bobyr, N.A. Milostnaya The article discusses the mechanism of adaptation of the input triangular membership functions used in the neuro-fuzzy system output. Bust input parameters of membership functions is proposed to carry out on the basis of genetic algorithm. In order to illustrate the operation of the genetic algorithm in the article the algorithm and an example of fi nding the maximum value of a given function. In this case, the basic operations of genetic algorithm are crossover and mutation, which are also used in the adaptation of fuzzy membership functions. It should be noted that the modifi cation operation crossovering and mutation of chromosomes respective fuzzy peaks used to change the membership functions of the respective chromosomes. In order to explain the operation of the proposed adaptation mechanism in the article discusses examples for MISO-fuzzy systems, which illustrate the essence of the proposed approach. Keywords: fuzzy logic; adaptive neuro-fuzzy inference system; genetic algorithm; fuzzy inference system. Contacts: E-mail: max_b@mail333.com Pp. 27-32.