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dc.contributor.authorAndrzej Pownuken_US
dc.contributor.authorVladik Kreinovichen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:26:35Z-
dc.date.available2018-09-05T04:26:35Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn21984190en_US
dc.identifier.issn21984182en_US
dc.identifier.other2-s2.0-85032701170en_US
dc.identifier.other10.1007/978-3-319-69989-9_14en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85032701170&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58593-
dc.description.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.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.subjectEngineeringen_US
dc.subjectMathematicsen_US
dc.subjectSocial Sciencesen_US
dc.titleFuzzy data processing beyond min t-normen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Systems, Decision and Controlen_US
article.volume125en_US
article.stream.affiliationsUniversity of Texas at El Pasoen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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