A fuzzy-neural network system and a learning method therein
作者： Takashi Aramaki , Teruhiko Matsuoka
DOI:
关键词: Layer (object-oriented design) 、 Control theory 、 Mathematics 、 Artificial neural network 、 Membership function 、 Algorithm 、 Range (statistics) 、 Learning methods 、 Value (computer science)
摘要: A fuzzy-neural network system includes: an input layer outputting values of parameters; a membership wherein multiple number regions for each the parameters are formed by dividing probable range parameter and function is defined regions, producing as to parameters, in accordance with output from layer; rule specific rules between belonging different suitability rules; or value setup means which, if some unknown, sets up prescribed corresponding unknown parameters.
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