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

In this paper, we generalize Ying’s model of linguistic quantifiers [M.S. Ying, Linguistic quantifiers modeled by Sugeno integrals, Artificial Intelligence, 170 (2006) 581-606] to intuitionistic linguistic quantifiers. An intuitionistic linguistic quantifier is represented by a family of intuitionistic fuzzy-valued fuzzy measures and the intuitionistic truth value (the degrees of satisfaction a...

This paper is a continuation of the first part of our study on type 〈1, 1〉 fuzzy quantifiers determined by fuzzy measures, in which the basic notions and examples were introduced. Here, we study the properties of permutation invariance and isomorphism invariance of fuzzy quantifiers determined by pairs of functionals (S, φ) and their special cases, e.g., fuzzy quantifiers defined by fuzzy measu...

This paper will introduce a new method to obtain the order weightsof the Ordered Weighted Averaging (OWA) operator. We will first show therelation between fuzzy quantifiers and neat OWA operators and then offer anew combination of them. Fuzzy quantifiers are applied for soft computingin modeling the optimism degree of the decision maker. In using neat operators,the ordering of the inputs is not...

this paper will introduce a new method to obtain the order weightsof the ordered weighted averaging (owa) operator. we will first show therelation between fuzzy quantifiers and neat owa operators and then offer anew combination of them. fuzzy quantifiers are applied for soft computingin modeling the optimism degree of the decision maker. in using neat operators,the ordering of the inputs is not...

Fuzzy quantifiers, i.e. operators intended to provide a numerical interpretation of natural language (NL) quantifiers like ‘almost all’, are valuable tools for image processing, in particular to express accumulative (second order) properties of fuzzy image regions. However, approaches to fuzzy quantification will unfold their full potential only if the proposed operators capture the meaning of ...

Fuzzy linguistic quantifiers – operators intended to model vague quantifying expressions in natural language like “almost all” or “few” – have gained importance as operators for information combination and the fusion of gradual evaluations. They are particularly appealing because of their ease-of-use: people are familiar with these operators, which can be applied for technical fusion purposes i...

This paper presents basic notions about fuzzy measures over algebras of fuzzy subsets of a fuzzy set. It also presents basic ideas on fuzzy integrals defined using these fuzzy measures. Definitions of new types of fuzzy measures and integrals are motivated by our research on generalized quantifiers. Several useful properties of fuzzy measures and fuzzy integrals are stated and proved. Definitio...

Many applications e.g. in approximate reasoning, data summarisation, information retrieval etc. can profit from the use of fuzzy quantifiers like “almost all” or “many”, which provide flexible means of information aggregation, and are capable of extracting meaningful linguistic summaries from large amounts of raw data. However, as will be shown by a number of counterexamples, existing approache...

The aim of this paper is to introduce monadic L-fuzzy quantifiers of the type 〈1, 1〉 and to investigate some of their semantic properties that are well-known in the generalized quantifier theory. Further, some relations between the semantic properties of generalized quantifiers are also studied for monadic L-fuzzy quantifiers. Finally, a property “to be extensional w.r.t. a given L-permutation ...