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Applied Mathematics and Computation
Article . 2006 . Peer-reviewed
License: Elsevier TDM
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An eigenvector method for generating normalized interval and fuzzy weights

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2006 China (People's Republic of) English Publisher:Elsevier BVJournal:Applied Mathematics and Computation, volume 181, pages 1,257-1,275 (issn: 0096-3003, Copyright policy )
Authors: Ying-Ming Wang 0001; Kwai-Sang Chin;

doi: 10.1016/j.amc.2006.02.026

An eigenvector method for generating normalized interval and fuzzy weights

Abstract

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Country
China (People's Republic of)
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Keywords

Management decision making, including multiple objectives, COMPARISON MATRICES, PREFERENCE, RANKING, multiple criteria decision making, ANALYTIC HIERARCHY PROCESS, PRIORITY DERIVATION, APPROXIMATE ARTICULATION, CONSISTENCY, 629, eigenvector, GOAL PROGRAMMING METHOD, normalization, PAIRWISE COMPARISON JUDGMENTS, interval comparison matrix, fuzzy comparison matrix, Theory of fuzzy sets, etc., analytic hierarchy process, DERIVING PRIORITIES

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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!
53
Top 10%
Top 10%
Average
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