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The Inference of Attribute Values Based on Fuzzy Reasoning

Author: WangJiKun
Tutor: LuShuXia；WangXiZhao
School: Hebei University
Course: Applied Mathematics
Keywords: Fuzzy measure Interaction Fuzzy integral Fuzzy production rules Fuzzy rule matrix transformation
CLC: O159
Type: Master's thesis
Year: 2008
Downloads: 14
Quote: 0
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Abstract


Fuzzy Production Rules (FPRs), which have been widely used in expert systems to represent fuzzy and uncertain concepts, are important tools in fuzzy reasoning. And fuzzy reasoning based on FPRs is a well-known reasoning method at present. To represent the fuzziness and uncertainty effectively and make the reasoning result more reasonable, some knowledge representation parameters, such as threshold value, certainty factor, local weight and globle weight are introduced.To a data base, a fuzzy rule set, which expresses the correlativity of attributes, can be received from the full patterns and experience. And the parameters of fuzzy rules are numbers. The reasoning algorithm based on fuzzy rule matrix transformation can be used to complete the incomplete pattern, and the new full can be used in training and synthetic judgment. And the investigations show that the method is effective in the real and has been widely used in Reasoning with Incomplete Knowledge.

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CLC: > Mathematical sciences and chemical > Mathematics > Algebra,number theory, portfolio theory > Fuzzy Mathematics
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