Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26776
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dc.contributor.authorWang, XZen_US
dc.contributor.authorWang, YDen_US
dc.contributor.authorXu, XFen_US
dc.contributor.authorLing, WDen_US
dc.contributor.authorYeung, DSen_US
dc.date.accessioned2015-06-23T09:12:26Z-
dc.date.available2015-06-23T09:12:26Z-
dc.date.issued2001-
dc.identifier.citationFuzzy sets and systems, 2001, v. 123, no. 3, p. 291-306en_US
dc.identifier.issn0165-0114-
dc.identifier.urihttp://hdl.handle.net/10397/26776-
dc.description.abstractThis paper proposes a new approach to fuzzy rule generation from a set of examples with fuzzy representation. The new approach called fuzzy extension matrix incorporates the fuzzy entropy to search for paths and generalizes the concept of crisp extension matrix. By discussing paths of the fuzzy extension matrix, a new heuristic algorithm for generating fuzzy rules is introduced. Compared with the crisp extension matrix, the proposed method has the capability of handling fuzzy representation and tolerating noisy data or missing data. A case study shows that the proposed heuristic algorithm partially inherits the advantages from the crisp case such as simplicity of rules and high learning accuracy. The proposed approach offers a new, practical way to automatically acquire imprecise knowledge.en_US
dc.description.sponsorshipDepartment of Computingen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofFuzzy Sets and Systemsen_US
dc.subjectExtension matrixen_US
dc.subjectFuzzy entropyen_US
dc.subjectHeuristic algorithmen_US
dc.subjectKnowledge acquisitionen_US
dc.subjectLearningen_US
dc.subjectLearning from fuzzy examplesen_US
dc.titleA new approach to fuzzy rule generation : fuzzy extension matrixen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage291-
dc.identifier.epage306-
dc.identifier.volume123-
dc.identifier.issue3-
dc.identifier.doi10.1016/S0165-0114(01)00002-1-
dc.identifier.scopus2-s2.0-0035501962-
dc.identifier.rosgroupidr07573-
dc.description.ros2001-2002 > Academic research: refereed > Publication in refereed journal-
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