نتایج جستجو برای: probabilistic hesitant fuzzy set
تعداد نتایج: 791087 فیلتر نتایج به سال:
The probabilistic fuzzy set (PFS) and the related probabilistic fuzzy logic system (PFLS) is designed for handling the uncertainties in both stochastic and nonstochastic nature. In this paper, a bell-shaped probabilistic fuzzy set is proposed and the related PFLS is constructed and applied to a modeling problem to study stochastic modeling capability. It clearly discloses that the bell-shaped P...
Decision making is a process common to human beings. The uncertainty and fuzziness of problems demand the use of the fuzzy linguistic approach to model qualitative aspects of problems related to decision. The recent proposal of hesitant fuzzy linguistic term sets supports the elicitation of comparative linguistic expressions in hesitant situations when experts hesitate among different linguisti...
The use of interval-valued hesitant fuzzy sets (IVHFS) can aid decision-makers in evaluating a variable using multiple interval numbers, making it valuable tool for addressing decision-making problems. However, fails to obtain information with greyness. grey set (GFS) improve this problem but studies on have lost the advantages IVHFS. In order accuracy and more reasonable results, is important ...
In the field of mechanical engineering, steam turbine fault diagnosis is a difficult task for mechanical engineers who are confronted with challenges in dealing with copious amounts of uncertain information. Different mechanical engineers may have their own opinions about the system fault knowledge base that differs slightly from other mechanical engineers. Thus, to solve the problems presented...
The weighted ordered weighted averaging(WOWA) operator introduced by Torra is an important aggregation technique, which includes the famous weighted averaging(WA) operator and the ordered weighted averaging(OWA) operator as special cases. In this paper, we introduce a new hesitant fuzzy decision making technique called the hesitant fuzzy weighted OWA(HFWOWA) operator. It is an extension of the ...
Since its original formulation, the theory of fuzzy sets has spawned a number of extensions where the role of membership values in the real unit interval $[0, 1]$ is handed over to more complex mathematical entities. Amongst the many existing extensions, two similar ones, the fuzzy multisets and the hesitant fuzzy sets, rely on collections of several distinct values to represent fuzzy membershi...
One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...
With respect to multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant fuzzy elements, the traditional grey relational projection (GRP) method is extended to solve multiple attribute decision making problems under hesitant fuzzy environment. Based on the hesitant fuzzy decision matrix provided by decision makers, all feasible alternatives are ...
The soft set theory is a newly mathematical tool to deal with uncertain problems. However, the classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. In this paper, we introduce the average function and propose the interval-valued intuitionistic hesitant fuzzy soft sets (IVIHFSSs) which are a combination of the interval-valued intuitionistic hesitant fuzzy sets and...
Fuzzy decision making is the collection of single or multicriteria techniques aiming at selecting the best alternative in case of imprecise, incomplete, and vague data. This chapter reviews the fuzzy decision making literature and summarizes the review results by tabular and graphical illustrations. The classification is based on the new extensions of fuzzy sets: Intuitionistic, hesitant, and t...
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