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dc.contributor.authorVladik Kreinovichen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T03:35:41Z-
dc.date.available2018-09-05T03:35:41Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85028459632en_US
dc.identifier.other10.1007/978-3-319-62434-1_17en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85028459632&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/57165-
dc.description.abstract© Springer International Publishing AG 2017. In the traditional fuzzy logic, the expert’s degree of certainty in a statement is described either by a number from the interval [0, 1] or by a subinterval of such an interval. To adequately describe the opinion of several experts, researchers proposed to use a union of the corresponding sets – which is, in general, more complex than an interval. In this paper, we prove that for such set-valued fuzzy sets, centroid defuzzification is equivalent to defuzzifying its interval hull. As a consequence of this result, we prove that the centroid defuzzification of a general type-2 fuzzy set can be reduced to the easier-to-compute case when for each x, the corresponding fuzzy degree of membership is convex.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleFor multi-interval-valued fuzzy sets, centroid defuzzification is equivalent to defuzzifying its interval hull: A theoremen_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume10061 LNAIen_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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