Polynomial regression interval-valued fuzzy systems |
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Authors: | Yu Qiu Hong Yang Yan-Qing Zhang Yichuan Zhao |
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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 |
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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. |
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Keywords: | Interval-valued fuzzy logic Type-2 fuzzy logic Statistical interval-valued fuzzy reasoning Fuzzy control |
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