Transformation Based Interpolation with Generalized Representative Values

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dc.contributor.author Shen, Qiang
dc.contributor.author Huang, Zhiheng
dc.date.accessioned 2008-01-23T14:16:14Z
dc.date.available 2008-01-23T14:16:14Z
dc.date.issued 2005
dc.identifier.citation Shen , Q & Huang , Z 2005 , ' Transformation Based Interpolation with Generalized Representative Values ' pp. 821-826 . en
dc.identifier.other PURE: 74525
dc.identifier.other dspace: 2160/468
dc.identifier.uri http://hdl.handle.net/2160/468
dc.description Z. Huang and Q. Shen. Transformation Based Interpolation with Generalized Representative Values. Proceedings of the 14th International Conference on Fuzzy Systems, pages 821-826. en
dc.description.abstract Fuzzy 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.extent 6 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Transformation Based Interpolation with Generalized Representative Values en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.identifier.doi http://dx.doi.org/10.1109/FUZZY.2005.1452500
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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