On Fuzzy Implication Functions Based on Admissible Orders on the Set of Discrete Fuzzy Numbers

Research on the construction of logical connectives using total (admissible) orders is a prolific area of study. Using such orders, a new method for constructing implication functions is defined on the set of discrete fuzzy numbers with support of a closed interval of a given finite chain and whose membership values belong to a finite set of fixed values. This method is based on the use of discrete implication functions defined on a finite chain. Furthermore, a bijective correspondence between the set of implication functions on the aforementioned subset of discrete fuzzy numbers and the set of discrete implication functions defined on the discrete chain is shown. Basic properties of these implication functions are thoroughly investigated, concluding that they are preserved under the proposed construction method. This result highlights the robustness and generality of the method, providing a systematic way to extend discrete implication functions to more complex structures while preserving their underlying properties.

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Publication Details

Journal
International Journal of Computational Intelligence Systems
Published
2025-06-02
DOI
https://doi.org/10.1007/s44196-025-00874-9
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
0.00

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article

On Fuzzy Implication Functions Based on Admissible Orders on the Set of Discrete Fuzzy Numbers

Juan Vicente Riera, Arnau Mir, Sebastià Massanet, Manuel González-Hidalgo et al.
International Journal of Computational Intelligence Systems
Multi-Criteria Decision Making
article

On Fuzzy Implication Functions Based on Admissible Orders on the Set of Discrete Fuzzy Numbers

Juan Vicente Riera, Arnau Mir, Sebastià Massanet, Manuel González-Hidalgo, Laura De Miguel
article en

Abstract

Research on the construction of logical connectives using total (admissible) orders is a prolific area of study. Using such orders, a new method for constructing implication functions is defined on the set of discrete fuzzy numbers with support of a closed interval of a given finite chain and whose membership values belong to a finite set of fixed values. This method is based on the use of discrete implication functions defined on a finite chain. Furthermore, a bijective correspondence between the set of implication functions on the aforementioned subset of discrete fuzzy numbers and the set of discrete implication functions defined on the discrete chain is shown. Basic properties of these implication functions are thoroughly investigated, concluding that they are preserved under the proposed construction method. This result highlights the robustness and generality of the method, providing a systematic way to extend discrete implication functions to more complex structures while preserving their underlying properties.

International Journal of Computational Intelligence SystemsVol. 18(1)
Universidad Pública de Navarra (UPNA) (ES), Health Research Institute of the Balearic Islands (ES), Universitat de les Illes Balears (ES)
Agencia Estatal de Investigación
Reduced inequalities
Openalex Percentile: Top 86%
Multi-Criteria Decision Making
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On Fuzzy Implication Functions Based on Admissible Orders on the Set of Discrete Fuzzy Numbers — Juan Vicente Riera, Arnau Mir, et al. · International Journal of Computational Intelligence Systems (2025) | TGRS Research Map | TGRS