提出了一种基于相似性的加权模糊产生规则计算方法.该方法允许权重与确定因子等参数用普通的语言词来表示,从而提高了模糊产生规则的知识表示力,使其更符合人们的思维习惯,为其应用提供了更大的范围.还提出了一种改进的方法来计算结果的模糊值及其确定因子,从而使计算结果更加合理.
[1] ZADEH L A. Outline of a new approach to the analysis of complex systems and decision processes [J]. IEEE Transactions on Systems Man and Cybernetics 1973, 3.
[2] TURKSEN I B, ZHONG Z. An approximate analogical reasoning scheme based on similarity measures and interval valued fuzzy sets [J]. Fuzzy Sets and Systems 1990, 34.
[3] Turksen I.B., Zhong Z.. An approximate analogical reasoning approach based on similarity measures [J]. IEEE transactions on systems, man, and cybernetics 1988, 6(6).
[4] YEUNG D S, TSANG E C C. Improved fuzzy knowledge representation and rule evaluation using fuzzy Petri nets and degree of subsethood [J]. Intell Syst 1994, 9(12).
[5] Yeung D.S., Tsang E.C.C.. A comparative study on similarity-based fuzzy reasoning methods [J]. IEEE transactions on systems, man, and cybernetics, Part B. Cybernetics: A publication of the IEEE Systems, Man, and Cybernetics Society 1997, 2(2).
[6] Chen S.-M.. A new approach to handling fuzzy decision-making problems [J]. IEEE transactions on systems, man, and cybernetics 1988, 6(6).
[7] CHEN S M. A weighted fuzzy reasoning algorithm for medical diagnosis [J]. Decision Support Systems 1994, 11.
[8] YEUNG D S, TSANG E C C. Weighted fuzzy production rules [J]. Fuzzy Sets and Systems 1997, 88.
[9] ZADEH L A. Fuzzy set [J]. Information and Control 1965, 8.
