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Polynomial regression interval-valued fuzzy systems
Authors:Yu Qiu  Hong Yang  Yan-Qing Zhang  Yichuan Zhao
Affiliation:(1) Department of Computer Science, Georgia State University, Atlanta, GA 30302-3994, USA;(2) Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA
Abstract:In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have implemented the proposed non-linear (polynomial regression) statistical interval-valued type-2 FLS to perform smart washing machine control. The results show that our quadratic statistical method is more robust to design a reliable type-2 FLS and also can be extend to polynomial model.
Keywords:Interval-valued fuzzy logic  Type-2 fuzzy logic  Statistical interval-valued fuzzy reasoning  Fuzzy control
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