The expected value and variance of a fuzzy variable have been well studied in the literature, and they provide important characterizations of the possibility distribution for the fuzzy variable. In this paper, we seek a similar characterization of the joint possibility distribution for a pair of fuzzy variables. In view of the success of introducing the expected value and variance as fuzzy inte...

In this paper we introduce the notion of levelwise convergence of sequence of fuzzy random variables. We derive equivalent conditions for left quasi uniform convergence of fuzzy random variables. Conditions are obtained for eventually equi-right continuity for the sequence of fuzzy random variables. A necessary and sufficient condition is obtained under which for a sequence of fuzzy random vari...

Fuzzy decision tree induction algorithms require the fuzzy quantization of the input variables. This paper demonstrates that supervised fuzzy clustering combined with similarity-based rule-simplification algorithms is an effective tool to obtain the fuzzy quantization of the input variables, so the synergistic combination of supervised fuzzy clustering and fuzzy decision tree induction can be e...

Fuzzy variables are functions from credibility spaces to the set of real numbers. Based on the expected value of a fuzzy variable, the expected value of function of a simple fuzzy variable is studied. In order further to discuss the mathematical properties of fuzzy variables, some inequalities for fuzzy variables are derived based on the concepts of credibility measures and expected value opera...

Several types of entropy of fuzzy variables or fuzzy sets have been given in the literature in order to measure the degree of uncertainty. In order to measure the degree of uncertainty of fuzzy vectors, a new definition of entropy of fuzzy vectors is proposed. Some properties are then investigated and the relations between the entropy of fuzzy variables and fuzzy vectors are discussed.

In this paper, we will discuss two special classes of mathematical programming models with fuzzy random variables. In the first model, a linear programming problem with fuzzy decision variables and fuzzy random coefficients is introduced. Then an algorithm is developed to solve the model based on fuzzy optimization method and fuzzy ranking method. In the second model, a fuzzy random quadratic s...

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

in this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. in other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. first, an analytical approach is proposed to simplify the structure of network. then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (tfn). this paper com...

Fuzziness plays an essential role in the real world. Fuzzy set theory has been developed very fast since it was introduced by Zadeh (1965) [1]. A fuzzy set was characterized with its membership function by Zadeh. The term fuzzy variable was fist introduced by Kaufmann (1975) [2], and then appeared in Zadeh (1978) [3] and Nahmias (1978) [4] as a fuzzy set of real numbers. In order to establish t...