On Nie-Tan Operator and Type-reduction of Interval Type-2 Fuzzy Sets

dc.cclicenceCC-BY-NCen
dc.contributor.authorJiawei, Lien
dc.contributor.authorJohn, Robert, 1955-en
dc.contributor.authorCoupland, Simonen
dc.contributor.authorGraham Kendallen
dc.date.acceptance2017-01-18en
dc.date.accessioned2017-02-08T10:01:41Z
dc.date.available2017-02-08T10:01:41Z
dc.date.issued2017-02-09
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractType-reduction of type-2 fuzzy sets is considered to be a defuzzification bottleneck because of the computational complexity involved in the process of type-reduction. In this research, we prove that the closed-form Nie-Tan operator, which outputs the average of the upper and lower bounds of the footprint of uncertainty, is actually an accurate method for defuzzifing interval type-2 fuzzy sets.en
dc.funderN/Aen
dc.identifier.citationLi, J., John, R., Coupland, S. and Kendall, G. (2017) On Nie-Tan Operator and Type-reduction of Interval Type-2 Fuzzy Sets., IEEE Transactions on Fuzzy Systems. 26 (2), pp. 1036-1039en
dc.identifier.doihttps://doi.org/10.1109/tfuzz.2017.2666842
dc.identifier.issn1941-0034
dc.identifier.urihttp://hdl.handle.net/2086/13227
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherIEEEen
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectFuzzy Logicen
dc.subjectDefuzzificationen
dc.titleOn Nie-Tan Operator and Type-reduction of Interval Type-2 Fuzzy Setsen
dc.typeArticleen

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