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Possibilistic evaluation of extended fuzzy rules in the presence of uncertainty

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dc.contributor.author Wallace, M en
dc.contributor.author Kollias, S en
dc.date.accessioned 2014-03-01T02:43:28Z
dc.date.available 2014-03-01T02:43:28Z
dc.date.issued 2005 en
dc.identifier.issn 10987584 en
dc.identifier.uri http://hdl.handle.net/123456789/31428
dc.subject Fuzzy Number en
dc.subject Fuzzy Rule Base en
dc.subject Fuzzy Rules en
dc.subject Rule Based System en
dc.subject.other Information analysis en
dc.subject.other Knowledge based systems en
dc.subject.other Number theory en
dc.subject.other Problem solving en
dc.subject.other Uncertain systems en
dc.subject.other Antecedents en
dc.subject.other Fuzzy numbers en
dc.subject.other Fuzzy rules en
dc.subject.other Fuzzy sets en
dc.title Possibilistic evaluation of extended fuzzy rules in the presence of uncertainty en
heal.type conferenceItem en
heal.identifier.primary 10.1109/FUZZY.2005.1452499 en
heal.identifier.secondary http://dx.doi.org/10.1109/FUZZY.2005.1452499 en
heal.publicationDate 2005 en
heal.abstract Characterization fuzzy in term ""fuzzy rule base"" is currently referred to the ability to define rule antecedents using fuzzy numbers. On the other hand, when it comes to the knowledge described by the rules and to the information contained in rule antecedents, absolute accuracy is assumed. With the emergence of a vast variety of applications of rule based systems, where antecedents are not provided by sensors but rather by complicated processing modules, more efficient rules and rule evaluation structures are needed, that are able to describe knowledge in more intuitive manner and cope with uncertainty in the assumed input. In this paper we propose extended fuzzy rules that allow for optional antecedents and provide a methodology for the possibilistic evaluation of both conventional and extended fuzzy rules in the presence of uncertainty. The work has been successfully applied in a real life problem, for which conventional fuzzy rules and fuzzy rule evaluation were inadequate. © 2005 IEEE. en
heal.journalName IEEE International Conference on Fuzzy Systems en
dc.identifier.doi 10.1109/FUZZY.2005.1452499 en
dc.identifier.spage 815 en
dc.identifier.epage 820 en


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