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dc.contributor.authorGreenfield, Sarahen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorDick, Scotten
dc.date.accessioned2016-07-11T10:33:12Z
dc.date.available2016-07-11T10:33:12Z
dc.date.issued2016
dc.identifier.citationGreenfield, S., Chiclana, F. and Dick, S. (2016) Join and Meet Operations for Interval-Valued Complex Fuzzy Logic. 35th North American Fuzzy Information Processing Society Annual Conference, NAFIPS 2016.en
dc.identifier.urihttp://hdl.handle.net/2086/12274
dc.descriptionDMU Interdisciplinary Group in Intelligent Transport Systemsen
dc.description.abstractInterval-valued complex fuzzy logic is able to handle scenarios where both seasonality and uncertainty feature. The interval-valued complex fuzzy set is defined, and the interval valued complex fuzzy inferencing system outlined. Highly pertinent to complex fuzzy logic operations is the concept of rotational invariance, which is an intuitive and desirable characteristic. Interval-valued complex fuzzy logic is driven by interval-valued join and meet operations. Four pairs of alternative algorithms for these operations are specified; three pairs possesses the attribute of rotational invariance, whereas the other pair lacks this characteristic.en
dc.language.isoenen
dc.subjectcomplex fuzzy logicen
dc.subjectinterval-valueden
dc.subjectseasonalityen
dc.subjectuncertaintyen
dc.subjectrotational invarianceen
dc.subjectjoin and meet operationsen
dc.titleJoin and Meet Operations for Interval-Valued Complex Fuzzy Logicen
dc.typeConferenceen
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.date.acceptance2016-06-11en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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