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  • A genetic algorithm to support learning fuzzy control rules from examples
    Filipič, Bogdan ; Juričić, Đani
    The paper presents an integration of Wang and Mendel's procedure for generating fuzzy rules from data and a genetic algorithm to learn fuzzy membership functions. The resulting system evolves ... numerical parameters of membership function definition as candidate solutions. For each solution the rule learning procedure is activated and the obtained fuzzy rules evaluated with respect to their performance on a given problem. As a result, both the membership function definitions and fuzzy rule base are generated from data records submitted to the system. The approach has been primarily developed to automate the construction of fuzzy controllers from traces of human operator control. Its utility is demonstrated in designing fuzzy control of the activated sludge process within a wastewater treatment plant.
    Vir: Genetic algorithms and soft computing (str. 403-418)
    Vrsta gradiva - članek, sestavni del
    Leto - 1996
    Jezik - angleški
    COBISS.SI-ID - 1989659

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