Interval type-2 fuzzy decision making

dc.cclicenceCC-BY-NC-NDen
dc.contributor.authorCoupland, Simonen
dc.contributor.authorRunkler, Thomasen
dc.contributor.authorJohn, Robert, 1955-en
dc.date.acceptance2016-09-23en
dc.date.accessioned2017-01-12T10:09:25Z
dc.date.available2017-01-12T10:09:25Z
dc.date.issued2016-09-23
dc.descriptionFull text on Nottingham eprints - http://eprints.nottingham.ac.uk/36609/en
dc.description.abstractThis paper concerns itself with decision making under uncertainty and the consideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature is limited in modelling decision making as there is no uncertainty in the membership function. We are interested in the role that interval type-2 fuzzy sets might play in enhancing decision making. Previous work by Bellman and Zadeh considered decision making to be based on goals and constraints. They deployed type-1 fuzzy sets. This paper extends this notion to interval type-2 fuzzy sets and presents a new approach to using interval type-2 fuzzy sets in a decision making situation taking into account the risk associated with the decision making. The explicit consideration of risk levels increases the solution space of the decision process and thus enables better decisions. We explain the new approach and provide two examples to show how this new approach works.en
dc.exception.reasonFull text version on University of Nottingham repositoryen
dc.funderN/Aen
dc.identifier.citationRunkler,T., Coupland. S., John, R. (2016) Interval type-2 fuzzy decision making. International Journal of Approximate Reasoning, 80, pp. 217-224en
dc.identifier.doihttps://doi.org/10.1016/j.ijar.2016.09.007
dc.identifier.urihttp://hdl.handle.net/2086/13164
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherElsevieren
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectFuzzy Logicen
dc.subjectGame Theoryen
dc.subjectDecisions under vagueness and risken
dc.titleInterval type-2 fuzzy decision makingen
dc.typeArticleen

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