Show simple item record Shen, Qiang Chen, Chenyuan 2011-09-26T10:05:06Z 2011-09-26T10:05:06Z 2011-09-26
dc.identifier.citation Shen , Q & Chen , C 2011 , ' Towards Fuzzy-Rough Rule Interpolation ' . en
dc.identifier.other PURE: 180026
dc.identifier.other dspace: 2160/7590
dc.description Chen, C., Shen, Q. (2011). Towards Fuzzy-Rough Rule Interpolation Proceedings of the 11th UK Workshop on Computational Intelligence(UKCI2011), 2011. en
dc.description.abstract Fuzzy rule interpolation is an important technique for performing inferences with sparse rule bases. Even when given observations have no overlap with the antecedent values of any rule, fuzzy rule interpolation may still derive a conclusion. Nevertheless, fuzzy rule interpolation can only handle fuzziness but not roughness. Rough set theory is a useful tool to deal with incomplete knowledge, which handles roughness but not fuzziness. Fuzzy rough sets are used to extend the original concepts in rough sets. This paper proposes a novel rule interpolation method which integrates fuzzy-rough representations with rule interpolation to deal with both fuzziness and roughness. The method follows the approach of [1],[2], using transformation-based techniques to perform interpolation, and can deal with rule interpolation in a more flexible and more robust way. en
dc.language.iso eng
dc.title Towards Fuzzy-Rough Rule Interpolation 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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