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dc.citation.endPage 180 -
dc.citation.number 2 -
dc.citation.startPage 177 -
dc.citation.title IEEE TRANSACTIONS ON FUZZY SYSTEMS -
dc.citation.volume 2 -
dc.contributor.author Bien, Zeungnam -
dc.contributor.author CHUN, MG -
dc.date.accessioned 2023-12-22T13:05:53Z -
dc.date.available 2023-12-22T13:05:53Z -
dc.date.created 2014-11-21 -
dc.date.issued 1994-05 -
dc.description.abstract An inference network is proposed as a tool for bidirectional approximate reasoning. The inference network can be designed directly from the given fuzzy data (knowledge). If a fuzzy input is given for the inference network, then the network renders a reasonable fuzzy output after performing approximate reasoning based on an equality measure. Conversely, due to the bidirectional structure, the network can yield its corresponding reasonable fuzzy input for a given fuzzy output. This property makes it possible to perform forward and backward reasoning in the knowledge base system -
dc.identifier.bibliographicCitation IEEE TRANSACTIONS ON FUZZY SYSTEMS, v.2, no.2, pp.177 - 180 -
dc.identifier.doi 10.1109/91.277965 -
dc.identifier.issn 1063-6706 -
dc.identifier.scopusid 2-s2.0-0028438837 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/9178 -
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0028438837 -
dc.identifier.wosid A1994PT98900007 -
dc.language 영어 -
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC -
dc.title AN INFERENCE NETWORK FOR BIDIRECTIONAL APPROXIMATE REASONING BASED ON AN EQUALITY MEASURE -
dc.type Article -
dc.description.journalRegisteredClass scopus -

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