出版社：Japan Society for Fuzzy Theory and Intelligent Informatics
摘要：This paper proposes a new fuzzy reasoning system with an entropy term as a regularization term in the objective function. Many studies have been done with fuzzy inference systems so far. Further, many improved models have been also proposed such as models using GA and self-organizing neural networks. The proposed fuzzy reasoning system has the objective function composed of the squared error and entropy terms: The former is the conventional objective one for the fuzzy reasoning system and the latter is a term which controls a shift of membership function. By adding the latter, learning of the system proceeds as degree of fitness of each rule approaches to 0.5. In order to demonstrate the validity of the proposed method, some numerical simulations are performed.
关键词：Entropy Term ; Fuzzy Reasoning Model ; Learning Method ; Squared Error
