Knowledge representation for fuzzy model composition

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dc.contributor.author Fu, Xin
dc.contributor.author Shen, Qiang
dc.date.accessioned 2008-01-07T11:22:22Z
dc.date.available 2008-01-07T11:22:22Z
dc.date.issued 2007-06
dc.identifier.citation Fu , X & Shen , Q 2007 , ' Knowledge representation for fuzzy model composition ' pp. 47-54 . en
dc.identifier.other PURE: 73788
dc.identifier.other dspace: 2160/401
dc.identifier.uri http://hdl.handle.net/2160/401
dc.description X. Fu and Q. Shen. 'Knowledge representation for fuzzy model composition', in Proceedings of the 21st International Workshop on Qualitative Reasoning, 2007, pp. 47-54. Sponsorship: EPSRC en
dc.description.abstract Compositional Modelling (CM) has been applied to synthesize automatically plausible scenarios in many problem domains with promising results. However, due to the lack of capability to deal with imprecise or illdefined information, there is a pressing need to improve the robustness and accuracy of the existing CM work. This paper presents a more flexible knowledge representation formalism that combines fuzzy set theory and recently developed CM methods to support automating the process of generating plausible scenario spaces. The proposed knowledge representation corporates both fuzzy parameters and fuzzy constraints into the representation of conventional model fragments. The fuzzy model composition process is illustrated by means of a simple worked example for aiding in crime investigation. en
dc.format.extent 8 en
dc.language.iso eng
dc.relation.ispartof en
dc.title Knowledge representation for fuzzy model composition 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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