Definition of Triangular Norms and Triangular Conorms on Subfamilies of Type-2 Fuzzy Sets

In certain stages of the application of a type-2 fuzzy logic system, it is necessary to perform operations between input or output fuzzy variables in order to compute the union, intersection, aggregation, complement, and so forth. In this context, operators that satisfy the axioms of t-norms and t-conorms are of particular significance, as they are applied to model intersection and union, respectively. Furthermore, the existence of a range of these operators allows for the selection of the t-norm or t-conorm that offers the optimal performance, in accordance with the specific context of the system. In this paper, we obtain new t-norms and t-conorms on some important subfamilies of the set of functions from [0,1] to [0,1]. The structure of these families provides a more solid algebraic foundation for the applications. In particular, we define these new operators on the subsets of the functions that are convex, normal, and normal and convex, as well as the functions taking only the values 0 or 1 and the subset of functions whose support is a finite union of closed intervals. These t-norms and t-conorms are generalized to the type-2 fuzzy set framework.

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Journal
Axioms
Published
2024-12-31
DOI
https://doi.org/10.3390/axioms14010027
Citations
1
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.35

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article

Definition of Triangular Norms and Triangular Conorms on Subfamilies of Type-2 Fuzzy Sets

Jorge Elorza, Carmen Torres-Blanc, Susana Cubillo, Francisco Javier Talavera et al.
1 citations
Axioms
Fuzzy Logic and Control Systems
0.35
article

Definition of Triangular Norms and Triangular Conorms on Subfamilies of Type-2 Fuzzy Sets

Jorge Elorza, Carmen Torres-Blanc, Susana Cubillo, Francisco Javier Talavera, Pablo Hernández-Varela
article en
1 citations

Abstract

In certain stages of the application of a type-2 fuzzy logic system, it is necessary to perform operations between input or output fuzzy variables in order to compute the union, intersection, aggregation, complement, and so forth. In this context, operators that satisfy the axioms of t-norms and t-conorms are of particular significance, as they are applied to model intersection and union, respectively. Furthermore, the existence of a range of these operators allows for the selection of the t-norm or t-conorm that offers the optimal performance, in accordance with the specific context of the system. In this paper, we obtain new t-norms and t-conorms on some important subfamilies of the set of functions from [0,1] to [0,1]. The structure of these families provides a more solid algebraic foundation for the applications. In particular, we define these new operators on the subsets of the functions that are convex, normal, and normal and convex, as well as the functions taking only the values 0 or 1 and the subset of functions whose support is a finite union of closed intervals. These t-norms and t-conorms are generalized to the type-2 fuzzy set framework.

AxiomsVol. 14(1)
San Sebastián University (CL), Universidad Politécnica de Madrid (ES), Universidad de Navarra (ES)
Universidad de Navarra, Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación, Asociación de Amigos de la Universidad de Navarra
Openalex Percentile: Top 30%
Fuzzy Logic and Control Systems
0.35
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