Abstract
In this paper, a probabilistic fuzzy logic system (PFLS) is discussed for modeling the stochastic and imprecise information. The PFLS uses a 3-dimensional probabilistic fuzzy set to capture the imprecise stochastic information. A unique 3-dimensional probabilistic fuzzy logic is designed to perform rule inference under such imprecise and stochastic environment. When the PFLS and neural networks are integrated in a unified framework, it can further adapt to time varying dynamics so as to improve its modeling performance. The paper briefly reviews this unique development and potential power of probabilistic fuzzy logic system.
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