Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58593
Title: Fuzzy data processing beyond min t-norm
Authors: Andrzej Pownuk
Vladik Kreinovich
Songsak Sriboonchitta
Keywords: Computer Science
Decision Sciences
Economics, Econometrics and Finance
Engineering
Mathematics
Social Sciences
Issue Date: 1-Jan-2018
Abstract: © 2018, Springer International Publishing AG. Usual algorithms for fuzzy data processing—based on the usual form of Zadeh’s extension principle—implicitly assume that we use the min “and”-operation (t-norm). It is known, however, that in many practical situations, other t-norms more adequately describe human reasoning. It is therefore desirable to extend the usual algorithms to situations when we use t-norms different from min. Such an extension is provided in this chapter.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85032701170&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/58593
ISSN: 21984190
21984182
Appears in Collections:CMUL: Journal Articles

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