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dc.contributor.author Shen, Qiang
dc.contributor.author Huang, Zhiheng
dc.date.accessioned 2008-01-15T20:48:46Z
dc.date.available 2008-01-15T20:48:46Z
dc.date.issued 2004
dc.identifier.citation Shen , Q & Huang , Z 2004 , ' Fuzzy interpolation with generalized representative values ' pp. 161-171 . en
dc.identifier.other PURE: 74768
dc.identifier.other dspace: 2160/429
dc.identifier.uri http://hdl.handle.net/2160/429
dc.description Z. Huang and Q. Shen. Fuzzy interpolation with generalized representative values. Proceedings of the 2004 UK Workshop on Computational Intelligence, pages 161-171. en
dc.description.abstract Fuzzy interpolative reasoning offers the potential to model problems using sparse rule bases, as opposed to dense rule bases deployed in traditional fuzzy systems. It thus supports the simplification of complex fuzzy models in terms of rule number and facilitates inferences when limited knowledge is available. This paper presents an interpolative reasoning method by means of scale and move transformations. It can be used to interpolate fuzzy rules involving arbitrarily complex polygonal fuzzy sets. In particular, the paper introduces the general definition on representative values (RVs) employed by fuzzy interpolation and presents three useful implementations of this definition. This provides a degree of freedom to choose appropriate RVs to meet different requirements. The interpolation mechanism associated with the general RV definition is outlined and a comparative study of the interpolation results over different RV implementations is given. en
dc.format.extent 11 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Fuzzy interpolation with generalized representative values en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Non peer reviewed en


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