We consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account. Furthermore, these systems take also fuzzy uncertainty into account by their fuzzy partitioning of input and ...

In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance to<b...

In this paper, we study how changes in the coefficients of objective function, the coefficients matrix and the right-hand-side vector of constraints of the fuzzy linear programming problems with the fuzzy order relation in the objective function and the constraints under ranking function affect the fuzzy optimal solution. We consider separate cases when changes occur in the data of the problem ...

the aim of this paper is the study of the sequence of join spacesand fuzzy subsets associated with a hypergroupoid. in thispaper we give some properties of the membership function$widetildemu_{otimes}$ corresponding to the direct pro-duct oftwo hypergroupoids and we determine the fuzzy grade of thehypergroupoid $langle htimes h, otimesrangle$ in a particularcase.

Abstract: In this paper we present the Beta function and its main properties. A key feature of the Beta function, which is given by the central-limit theorem, is also shown. We then introduce a new category of neural networks based on a new kernel: the Beta function. Next, we investigate the use of Beta fuzzy basis functions for the design of fuzzy logic systems. The functional equivalence betw...

A novel function-link fuzzy cerebelarmodel-articulation-controller (CMAC) is developed in this study. It is a generalization of a fuzzy neural network and of a conventional CMAC. Then, a control system comprising a function-link fuzzy CMAC and a fuzzy compensator is proposed for multi-input multi-output (MIMO) nonlinear chaotic systems. The function-link fuzzy CAMC is used to mimic an ideal con...

Fuzzy random variable is a measurable function from a probability space to the set of fuzzy variables, while random fuzzy variable is a function from a credibility space to the set of random variables. The concepts of independent and identically distributed fuzzy random variables and random fuzzy variables are presented, and some useful properties are discussed.