based on credibilistic value-at-risk (cvar) of regularfuzzy variable, we introduce a new cvar reduction method fortype-2 fuzzy variables. the reduced fuzzy variables arecharacterized by parametric possibility distributions. we establishsome useful analytical expressions for mean values and secondorder moments of common reduced fuzzy variables. the convex properties of second order moments with ...

Fuzzy random variables possess several interpretations. Historically, they were proposed either as a tool for handling linguistic label information in statistics or to represent uncertainty about classical random variables. Accordingly, there are two different approaches to the definition of the variance of a fuzzy random variable. In the first one, the variance of the fuzzy random variable is ...

In this paper, a fuzzy finite element method (FFEM) for determining the responses of structures is proposed by using transformation between and random variables. Firstly, formulae establishing normal variables equivalent to symmetric triangular numbers are presented based on combination principle insufficient reason that maximum specificity. As result, analysis transferred into stochastic analy...

Fuzzy models describe nonlinear input-output relationships with linguistic fuzzy rules. A hierarchical fuzzy modeling is promising for identification of fuzzy models of target systems that have many input variables. In the identification, (1) determination of a hierarchical structure of submodels, (2) selection of input variables of each submodel, (3) division of input and output space, (4) tun...

In this paper, the so-called Wang–Mendel (WM) method for generating fuzzy rules from data is enhanced to make it a comprehensive and flexible fuzzy system approach to data description and prediction. In the description part, the core ideas of the WM method are used to develop three methods to extract fuzzy IF–THEN rules from data. The first method shows how to extract rules for the user-specife...

We firstly introduce an evaluation method of fuzzy numbers called the mean value with evaluation measures. Then, using this notion, a stopping game model with fuzzy random variables could be formulated. When a sequence of fuzzy-valued random variables(fuzzy RV) are observed, the important problem is how to treat and analyze the model. Previously the observed fuzzy RV’s are evaluated by probabil...