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Transitive Closures of Ternary Fuzzy Relations

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2021 Belgium English Publisher:Springer Science and Business Media LLCJournal:International Journal of Computational Intelligence Systems, volume 14, page 1,784 (eissn: 1875-6883, Copyright policy )
Authors: Zedam, Lemnaouar; De Baets, Bernard;

doi: 10.2991/ijcis.d.210607.001

handle: 1854/LU-8715191

Transitive Closures of Ternary Fuzzy Relations

Abstract

Recently, we have introduced six types of composition of ternary fuzzy relations. These compositions are close in spirit to the composition of binary fuzzy relations. Based on these types of composition, we have introduced several types of transitivity of a ternary fuzzy relation and investigated their basic properties. In this paper, we prove additional properties and characterizations of these types of transitivity of a ternary fuzzy relation. Also, we provide a representation theorem for ternary fuzzy relations satisfying these types of transitivity. Finally, we focus on the problem of closing a ternary fuzzy relation with respect to the proposed types of transitivity.

Country
Belgium
Related Organizations
Keywords

Ternary fuzzy relation, REPRESENTATION, General Computer Science, QA75.5-76.95, Computational Mathematics, transitive closure, Mathematics and Statistics, Electronic computers. Computer science, relational composition, transitivity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold