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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Qiu, Y., Yang, H., Zhang, YQ. et al. Polynomial regression interval-valued fuzzy systems. Soft Comput 12, 137–145 (2008). https://doi.org/10.1007/s00500-007-0189-4
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DOI: https://doi.org/10.1007/s00500-007-0189-4