Abstract
Examines a successful method which has been developed for integrating neural nets and fuzzy logic. Outlines the background of fuzzy logic and neural net design techniques, highlighting their strengths and weaknesses. Describes the importance of the error back propagation algorithm in neural net applications and how the difficulties of applying it to a fuzzy logic system were overcome in the NueuroFuzzy Module by using an extended fuzzy logic inference method that employs so‐called fuzzy associative memories [FAMs]. Describes the development steps of NeuroFuzzy systems and gives an example application of such a system to reduce water and energy consumption of washing machines. Concludes with other applications for NeuroFuzzy systems, including the optimization of a biological fermentation process and speaker‐independent speech recognition.
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