Host: Japan SOciety for Fuzzy Theory and intelligent informatics
Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"
Studies on the effectiveness of fuzzy logic for nonlinear modeling is presented. Although successful applications of fuzzy logic in many diverse areas are reported in the literature, commonly the explicit description of the key features of fuzzy logic yielding these outcomes is not addressed. The present research addresses this issue, to understand the basic features of fuzzy logic in nonlinear modeling applications in the context of dynamic system modeling, data modeling, signal modeling etc. This is accomplished by stochastic inputs to a nonlinear system modeled by fuzzy logic. The modeling performance is investigated in relation to the degree of nonlinearity of the model and the probability density of the stochastic inputs.
