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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 IEEE Potentialsarrow_drop_down
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
IEEE Potentials
Article . 1996 . Peer-reviewed
License: IEEE Copyright
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Using fuzzy set theory

Authors: C. Radu; R. Wilkerson;

Using fuzzy set theory

Abstract

Two main trends are mentioned: the fuzzy set theory and the fuzzy logic. Both build upon set theory and logic, respectively. Three features distinguish the approaches: (1) the use of so called linguistic variables, instead of or together with numeric variables; (2) the use of fuzzy conditional statements to represent simple relations between variables; and (3) the characterization of complex relations by fuzzy algorithms. Fuzzy linguistic variables and fuzzy algorithms offer an effective, more flexible way to describe a system's behavior too complex for a classical mathematical model. They are very successful in economics, management science, artificial intelligence, information retrieval systems, pattern recognition, image processing, psychology, biology, and other fields rendered inherently fuzzy do to the unpredictable behavior of their components. Expert systems, fuzzy neural computing and pattern recognition are discussed in some detail.

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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!
4
Average
Top 10%
Average
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