Data di Pubblicazione:
2016
Abstract:
The fuzzy theory is a generalization of the standard set theory that is based on the membership function, which expresses, in the fuzzy sense, the membership degree of an element to a set. After a review of the main operations on fuzzy sets, some applications are proposed in various contexts such as in engineering sciences or computational sciences, in automatic systems control or quality evaluation. Special attention is devoted to the applications of fuzzy theory in cognitive sciences by highlighting various critical issues reported in the literature and some responses to these. The intuitionistic and hesitant settings are then introduced and it is shown how these operate the union and intersection of fuzzy sets. In the intuitionistic fuzzy theory; along with a membership function, a non-membership function is defined and uncertainty is modeled. Besides, the hesitant fuzzy theory allows to express the uncertainty of one or more decision makers.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Cognitive science; Computer science; Fuzzy sets; Hesitant fuzzy sets; Intuitionistic fuzzy sets; Quality evaluation; Language and Linguistics; Experimental and Cognitive Psychology; Linguistics and Language; Cognitive Neuroscience; Artificial Intelligence
Elenco autori:
Marasini, Donata; Quatto, Piero; Ripamonti, Enrico
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