Statistical interval-valued fuzzy systems via linear regression

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. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple statistical linear method to decide interval-valued fuzzy membership functions and a new probability type reduce reasoning method for the interval-valued fuzzy logic system are proposed in this paper. An example of statistical interval-valued FLS is performed and results show that the developed method is more accurate to design a fuzzy logic system than type-1 method and computation is efficient.