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dc.contributor.author Shen, Qiang
dc.contributor.author Yang, Longzhi
dc.date.accessioned 2011-09-26T10:04:25Z
dc.date.available 2011-09-26T10:04:25Z
dc.date.issued 2011-09-26
dc.identifier.citation Shen , Q & Yang , L 2011 , ' Adaptive Fuzzy Interpolation with Uncertain Observations and Rule Base ' pp. 471-478 . en
dc.identifier.other PURE: 180195
dc.identifier.other dspace: 2160/7589
dc.identifier.uri http://hdl.handle.net/2160/7589
dc.description L. Yang and Q. Shen, Adaptive fuzzy interpolation with uncertain observations and rule base, Proceedings of the 20th International Conference on Fuzzy Systems (FUZZ-IEEE 2011), pp.471-478, 2011. en
dc.description.abstract Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning. It views interpolation procedures as artificially created system components, and identifies all possible sets of faulty components that may each have led to all detected contradictory results. From this, a modification procedure takes place, which tries to modify each of such components, termed candidates, in an effort to remove all the contradictions and thus restore consistency. This approach assumes that the employed interpolation mechanism is the only cause of contradictions, that is all given observations and rules are believed to be true and fixed. However, this may not be the case in certain real situations. It is common in fuzzy systems that each observation or rule is associated with a certainty degree. This paper extends the adaptive approach by taking into consideration both observations and rules also, treating them as diagnosable and modifiable components in addition to interpolation procedures. Accordingly, the modification procedure is extended to cover the cases of modifying observations or rules in a given rule base along with the modification of fuzzy reasoning components. This extension significantly improves the robustness of the existing adaptive approach. en
dc.format.extent 8 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Adaptive Fuzzy Interpolation with Uncertain Observations and Rule Base 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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