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https://doi.org/10.1109/fuzzy....
Article . 2006 . Peer-reviewed
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https://dx.doi.org/10.1109/fuz...
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The Linguistic Weighted Average

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Jan 2006Publisher:IEEEJournal:2006 IEEE International Conference on Fuzzy Systems
Authors: Dongrui Wu; Jerry M. Mendel;

doi: 10.1109/fuzzy.2006.1681768

The Linguistic Weighted Average

Abstract

The focus of this paper is the linguistic weighted average (LWA), which is a generalization of the fuzzy weighted average (FWA) that is obtained by replacing the type-1 fuzzy inputs in the FWA by interval type-2 fuzzy sets (IT2 FSs). Consequently, the output of the LWA is an IT2 FS. In this paper, the relations between the LWA and the FWA are studied. It is shown that finding the LWA can be decomposed into finding two FWAs, where alpha-cuts and KM algorithms are used. Hence, the computational cost of a LWA is about twice that of a FWA. A flowchart for computing the LWA is also provided.

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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
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