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International Journal of Intelligent Systems
Article . 2001 . Peer-reviewed
License: Wiley TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 2001
Data sources: zbMATH Open
DBLP
Article . 2001
Data sources: DBLP
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Fuzzy reasoning based on the extension principle

Authors: Yang Xu 0001; Etienne E. Kerre; Da Ruan 0001; Zhenming Song;

Fuzzy reasoning based on the extension principle

Abstract

Summary: According to the operation of decomposition (also known as representation theorem) [\textit{C. V. Negoita} and \textit{D. A. Ralescu}, Kybernetes 4, 169-174 (1975; Zbl 0352.02044)] in fuzzy set theory, the whole fuzziness of an object can be characterized by a sequence of local crisp properties of that object. Hence, any fuzzy reasoning could also be implemented by using a similar idea, i.e., a sequence of precise reasoning. More precisely, we could translate a fuzzy relation ``If \(A\) then \(B\)'' of the generalized modus ponens rule (the most common and widely used interpretation of a fuzzy rule, \(A\), \(B\), are fuzzy sets in a universe of discourse \(X\), and of discourse \(Y\), respectively) into a corresponding precise relation between a subset of \(P(X)\) and a subset of \(P(Y)\), and then extend this corresponding precise relation to two kinds of transformations between all \(L\)-type fuzzy subsets of \(X\) and those of \(Y\) by using Zadeh's extension principle, where \(L\) denotes a complete lattice. In this way, we provide an alternative approach to the existing compositional rule of inference, which performs fuzzy reasoning based on the extension principle. The approach does not depend on the choice of fuzzy implication operator nor on the choice of a t-norm. The detailed reasoning methods, applied in particular to the generalized modus ponens and the generalized modus tollens, are established and their properties are further investigated in this paper.

Related Organizations
Keywords

fuzzy sets, fuzzy information, Reasoning under uncertainty in the context of artificial intelligence

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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!
14
Average
Top 10%
Average
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