Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or de...

fuzzy decision tree (fdt) classifiers combine decision trees with approximate reasoning offered by fuzzy representation to deal with language and measurement uncertainties. when a fdt induction algorithm utilizes stopping criteria for early stopping of the tree's growth, threshold values of stopping criteria will control the number of nodes. finding a proper threshold value for a stopping crite...

‎a new method for the defuzzification of fuzzy numbers is developed in this paper. it is well-known, defuzzification methods allow us to find aggregative crisp numbers or crisp set for fuzzy numbers. but different fuzzy numbers are often converted into one crisp number. in this case the loss of essential information is possible. it may result in inadequate final conclusions, for example, expert...

Fuzzy distance is applied on data analysis, classification, and product positioning analysis widely. In this paper, We introduce a fuzzy distance by using graded mean integration representation of generalized fuzzy number and the span of fuzzy number, We also discuss the distance of the linguistic data of “greater or less than x” and “about x”. It is reasonable to say “the fuzzy distance of abo...

The fundamental concept of the fuzzy logic has been weakened by requiring a mere membership relation; consequently an ordered fuzzy number (OFN) arises as an ordered pair of continuous real functions defined on the interval [0, 1]. Four algebraic operations are constructed in a way that renders them an algebra. Further, a norm is introduced which makes them a Banach space. A class of linear def...

We studied here on some simple examples the interaction between valuation family, parameters and ranking result. The ranking method studied is based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. The valuation method considered was introduced initially by the Yager and Filev. This valuation consists in...

This paper develops a two-stage Cournot production game that integrates strategic and operational planning under the fuzzy random environment, which to our best knowledge has not appeared in the literature. At the strategic level, two competing decision-makers determine the upper bound of a production quantity under a high-production strategy and the lower bound of the production quantity under...

In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...

Introduction: In many applications, ranking of fuzzy numbers is an important component of the decision process. Many authors have investigated the use of fuzzy sets in ranking alternatives and they have studied different methods of raking fuzzy sets. Particularly, the ranking of fuzzy numbers. In a paper by Cheng [A new approach for ranking fuzzy numbers by distance method, Fuzzy Sets and Syste...