Adaptive Fuzzy Interpolation and Extrapolation with Multiple-antecedent Rules

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dc.contributor.author Shen, Qiang
dc.contributor.author Yang, Longzhi
dc.date.accessioned 2010-07-27T14:12:42Z
dc.date.available 2010-07-27T14:12:42Z
dc.date.issued 2010-07-27
dc.identifier.citation Shen , Q & Yang , L 2010 , ' Adaptive Fuzzy Interpolation and Extrapolation with Multiple-antecedent Rules ' pp. 565-572 . en
dc.identifier.other PURE: 159304
dc.identifier.other dspace: 2160/4873
dc.identifier.uri http://hdl.handle.net/2160/4873
dc.description L. Yang and Q. Shen. Adaptive Fuzzy Interpolation and Extrapolation with Multiple-antecedent Rules. Proceedings of the 19th International Conference on Fuzzy Systems (FUZZ-IEEE'10), pp. 565-572, 2010. en
dc.description.abstract Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning owning to its efficient identification and correction of defective interpolated rules during the interpolation process [11]. This approach assumes that: i) two closest adjacent rules which flank the observation or a previously inferred result are always available; ii) only single-antecedent rules are involved. In practice, however, variable values of these rules may lie just on one side of the observation or inferred result. Also, there may be certain rules with multiple antecedents in the rule base. This paper extends the adaptive approach, in order to cover fuzzy extrapolation and to support rule base with multiple-antecedent rules. Adaptive fuzzy interpolation and extrapolation complement each other, which jointly improve the applicability of fuzzy interpolative reasoning, as it significantly reduces the restriction over the given rule base. en
dc.format.extent 8 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Adaptive Fuzzy Interpolation and Extrapolation with Multiple-antecedent Rules en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.description.status Non peer reviewed en


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