Fuzzy set-theoretic operators and quantifiers (Q2702358)

From MaRDI portal





scientific article
Language Label Description Also known as
English
Fuzzy set-theoretic operators and quantifiers
scientific article

    Statements

    0 references
    0 references
    3 December 2001
    0 references
    survey
    0 references
    aggregation operators
    0 references
    fuzzy set-theoretic operators and quantifiers
    0 references
    fuzzy sets
    0 references
    connectives
    0 references
    fuzzy logics
    0 references
    uninorms
    0 references
    OWA operators
    0 references
    root-power mean operators
    0 references
    symmetric sums
    0 references
    linguistic quantifiers
    0 references
    Fuzzy set-theoretic operators and quantifiers (English)
    0 references
    This chapter in Kluwer's handbook series devoted to fuzzy sets brings an overview of fuzzy set-theoretic operators and quantifiers. First of all, basic operations for fuzzy sets as well as connectives for fuzzy logics are discussed, such as negation (complementation), conjunction (intersection), disjunction (union), implication, coimplication, equivalence, etc. The authors present here basic characterization results for several unary and binary operations, including most important examples. Note that t-norms (models for fuzzy conjunction) and related operations are, in an exhaustive form, discussed also in a recent monograph of \textit{E. P. Klement}, \textit{R. Mesiar} and \textit{E. Pap} [Triangular norms, Kluwer Academic Publishers, Dordrecht (2000; Zbl 0972.03002)]. Several other operators frequently applied in applications of fuzzy set theory (e.g., in fuzzy control) are also recalled, such as uninorms, OWA operators, root-power mean operators, symmetric sums, etc. Also, several types of quantifiers, especially linguistic quantifiers (``most'', ``few'', ``almost all'', etc.) are included. Finally, prioritized fuzzy operations are discussed.NEWLINENEWLINENEWLINEThis contribution is a good state-of-the-art overview with more than 120 relevant references and it can be recommended to any user or person interested in fuzzy sets and their applications.NEWLINENEWLINEFor the entire collection see [Zbl 0942.00007].
    0 references
    0 references

    Identifiers