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dc.contributor.authorHuang, Zhiheng
dc.contributor.authorShen, Qiang
dc.coverage.spatial7en
dc.date.accessioned2006-05-02T17:14:45Z
dc.date.available2006-05-02T17:14:45Z
dc.date.issued2005
dc.identifier.citationZ. H. Huang and Q. Shen. Transformation based interpolation with generalized representative values. In Proc. of the International Conference on Fuzzy Systems, pages 821 – 826, 2005.en
dc.identifier.urihttp://hdl.handle.net/1842/907
dc.description.abstractFuzzy interpolation offers the potential to model problems with sparse rule bases, as opposed to dense rule bases deployed in traditional fuzzy systems. It thus supports the simplification of complex fuzzy models and facilitates inferences when only limited knowledge is available. This paper first introduces the general concept of representative values (RVs), and then uses it to present an interpolative reasoning method which can be used to interpolate fuzzy rules involving arbitrary polygonal fuzzy sets, by means of scale and move transformations. Various interpolation results over different RV implementations are illustrated to show the flexibility and diversity of this method. A realistic application shows that the interpolation-based inference can outperform the conventional inferences.en
dc.format.extent2057148 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEEen
dc.subjectFuzzy interpolationen
dc.subjectfuzzy modelsen
dc.subjectrepresentative valuesen
dc.titleTransformation Based Interpolation with Generalized Representative Valuesen
dc.typeArticleen


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