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International Journal of Intelligent Systems
Article . 2003 . Peer-reviewed
License: Wiley TDM
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Aggregation of T-transitive relations

Authors: Jacas Moral, Juan; Recasens Ferrés, Jorge;

Aggregation of T-transitive relations

Abstract

This article studies the aggregation of transitive fuzzy relations. We first find operators that preserve transitivity and then extend the results to aggregating operators. As special cases, means and some kind of suitable ordered weighted averaging (OWAs) are used to aggregate transitive fuzzy relations with respect to an Archimedean t-norm. Three families of transitive relations that allow us to modify the entries of a given relation R continuously towards the smallest and the greatest ones in our universe are given. Aggregation of nonfinite families of transitive relations also is studied and applied to calculate the degree of inclusion or similarity of fuzzy quantities (fuzzy subsets of an interval of the real line). © 2003 Wiley Periodicals, Inc.

Keywords

Àrees temàtiques de la UPC::Matemàtiques i estadística::Lògica matemàtica, Fuzzy logic, Lògica difusa, Pattern recognition, speech recognition, :Matemàtiques i estadística::Lògica matemàtica [Àrees temàtiques de la UPC], Fuzzy logic; logic of vagueness, transitive fuzzy relations

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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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
35
Top 10%
Top 10%
Average
47
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