A characterization of linearly compensated hybrid connectives used in fuzzy classifications

Mónica Sańchez, Francesc Prats, Núria Agell, Joseph Aguilar-Martin

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

1 Citació (Scopus)

Resum

The study of linearly compensated hybrid connectives H = C+(1¡) C, where C is a t-norm and C represents the dual connective of C, to define aggregation operators for fuzzy classifications is a key point not only in fuzzy sets theory but also in learning processes. Although these operators are not associative, the fact that they can be decomposed into associative functions easily gives rise to n-Ary aggregation functions by straightforward iteration. Among the most commonly used t-norms are those of Frank's family, which are simultaneously t-norms and copulas. The purpose of this paper is to give a characterization of the hybrid connective H, via the properties of the connective C. Necessary and sufficient conditions of H that define C as a copula are given. The characterized hybrid connectives H are used to compute the global adequacy degree of an object in a class from marginal adequacy degrees in a learning system.

Idioma originalAnglès
Títol de la publicacióECAI 2004 - 16th European Conference on Artificial Intelligence, including Prestigious Applications of Intelligent Systems, PAIS 2004 - Proceedings
EditorsRamon Lopez de Mantaras, Lorenza Saitta
EditorIOS Press
Pàgines1081-1082
Nombre de pàgines2
ISBN (electrònic)9781586034528
Estat de la publicacióPublicada - 2004
Esdeveniment16th European Conference on Artificial Intelligence, ECAI 2004 - Valencia, Spain
Durada: 22 d’ag. 200427 d’ag. 2004

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
Volum110
ISSN (imprès)0922-6389

Conferència

Conferència16th European Conference on Artificial Intelligence, ECAI 2004
País/TerritoriSpain
CiutatValencia
Període22/08/0427/08/04

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