Generalization of QL-operators based on general overlap and general grouping functions

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Date
2022Author
Version
Acceso abierto / Sarbide irekia
Type
Contribución a congreso / Biltzarrerako ekarpena
Version
Versión aceptada / Onetsi den bertsioa
Impact
|
10.1109/FUZZ-IEEE55066.2022.9882638
Abstract
Firstly, this work discusses the main conditions
guarantying that general overlap (grouping) functions can be
obtained from n-dimensional overlap (grouping) functions. Focusing on QL-implications, which are usually generated by strong
negations together with t-norms and t-conorms, we consider a
non-restrictive construction, by relaxing not only the associativity
and the corresponding neutral ...
[++]
Firstly, this work discusses the main conditions
guarantying that general overlap (grouping) functions can be
obtained from n-dimensional overlap (grouping) functions. Focusing on QL-implications, which are usually generated by strong
negations together with t-norms and t-conorms, we consider a
non-restrictive construction, by relaxing not only the associativity
and the corresponding neutral elements (NE) but also the reverse
construction of other properties. Thus, the main properties of the
QL-implication class are studied, considering a tuple (G,N,O)
generated from grouping and overlap functions together with
the greatest fuzzy negation. In addition, in order to provide more
flexibility, we define a subclass of QL-implications generated from
general overlap and general grouping functions. Some examples
are introduced, illustrating the constructive methods to generate
such operators. [--]
Subject
Aggregation function,
Fuzzy Implication,
General Grouping Function,
General Overlap Function,
QL-implication
Publisher
IEEE
Published in
IEEE International Conference on Fuzzy Systems. 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2022 p. 1-8
Departament
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Publisher version
Sponsorship
This work was partially supported by CAPES, UFERSA, PQ/CNPq (309160/2019-7; 311429/2020-3), PqG/FAPERGS (21/2551-0002057-1) and FAPERGS/CNPq PRONEX (16/2551-0000488-9).
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