Real world applications often require dealing with the situations in which the exact numerical values of the (sub)measure of a set may not be provided, but at least some probabilistic assignment still could be done. Also, several concepts in uncertainty processing are linked to the processing of distribution functions. In the framework of generalized measure theory we introduce the probabilisti...

The fuzzy modeling technology, which uses a rule-based description of the relationship between variables, is discussed. We then turn to the problem of the simultaneous solution of relationships involving fuzzy models. We illustrate this problem by considering the equilibrium problem in economics. In this case we have two relationships, one between price and supply and the other between price an...

We introduced and study fuzzy Γ-hypersemigroups, according to fuzzy semihypergroups as previously defined [33] and prove that results in this respect. In this regard first we introduce fuzzy hyperoperation and then study fuzzy Γ-hypersemigroup. We will proceed by study fuzzy Γ-hyperideals and fuzzy Γ-bihyperideals. Also we study the relation between the classes of fuzzy Γ-hypersemigroups and Γ-...

The aim of this paper is to study monadic L-fuzzy quantifiers of the type 〈1〉 determined by fuzzy measures. These fuzzy quantifiers are defined using a novel notion of ⊗-fuzzy integral. Several semantic properties of these L-fuzzy quantifiers are studied. Keywords— fuzzy integral, fuzzy logic, fuzzy measure, fuzzy quantifier, generalized quantifier

This paper discusses fuzzification of crisp domains into fuzzy classes providing fuzzy domains. Relationship between two fuzzy domains, Xi and Xj , is represented by a matrix, wij . If Xi and Xj have n and m elements of fuzzy data, respectively, then wij is n × m matrix. The primary goal of the paper is to generate and provide some formulas for predicting interval probability in the relation to...

The Dempster–Shafer theory (DST) may be considered as a generalization of the probability theory, which assigns mass values to the subsets of the referential set and suggests an interval-valued probability measure. There have been several attempts for fuzzy generalization of the DST by assigning mass (probability) values to the fuzzy subsets of the referential set. The interval-valued probabili...

We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a given, labeled data set. The presented method is therefore best suited for applications where the focus of analysis lies on a model for the minority class or for smallto medium-size data sets. The clustering algorithm creates one-dimensional models of the neighborhood for a set of patterns by cons...

In many personnel evaluation scenarios, decision makers are asked to provide their preferences anonymously to both ensure privacy and avoid psychic contagion. The use of hesitant fuzzy sets is a powerful technique for representing this type of information and has been well studied. This paper explores aggregation methods for prioritized hesitant fuzzy elements and their application on personnel...

In 2011 Alkhazaleh and Salleh defined the concept of soft expert sets where the user can know the opinion of all the experts in one model and give an application of this concept in decision-making problems. Also, they introduced the concept of the fuzzy soft expert set as a combination between the soft expert set and the fuzzy set. In 2010 Majumdar and Samanta presented the concept of a general...