Abstract
It is a well know problem of the conventional fuzzy reasoning that the fuzziness of inferred results gradually increases accprding to the progress of the inference. In this paper, we discuss a combination function which can reduce the fuzziness measured as the degree of crisp. Essential problems are (1) the combined result obtained with a conventional combination function becomes close to one of the two non-fuzzy values, that is, grade 0 or 1,and never approaches to the other non-fuzzy value, and (2) lack of reinforcement property. We proposed a new combination function which resolves the problems by introducing equilibrium E and dependency factors a and b. In this paper, first, the basic idea and the calculation flow are briefly explained. Aecondly, semantics of the parameters and the coverage of the function are described as important features. Finally, the learning process of the parameters is demonstrated by using the fuzzy inference software environment called FINEST which is being developed at the Laboratory for International Fuzzy Engineering Research in Japan.
