About Premise Reduction of Fuzzy Inference Algorithm

被引:0
作者
Zhang, Cheng-yi [1 ]
Niu, Qi [2 ]
Peng, De-jun [1 ]
Li, Juan [1 ]
机构
[1] Hainan Normal Univ, Dept Math, Haikou 571158, Hainan, Peoples R China
[2] Zhumadian Educ Coll, Dept Math, Zhumadian 463000, Henan, Peoples R China
关键词
Fuzzy inference; SMTT fuzzy inference algorithm; Weighted-objective nearness degree;
D O I
10.1007/s12543-009-0019-8
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The comprehensive model with "weighted-objective nearness degree" is introduced in the process of multi-objective decision-making, by which a reduction problem of inference antecedents is studied in traditional fuzzy inference method. Moreover, based on the comprehensive model with "weighted-objective nearness degree" SMTT fuzzy inference algorithm is proposed. This algorithm not only shows the relative importance of every antecedent component in fuzzy inference, but also considers the influence of nearness degree between every antecedent component's evaluation and inference objective on inference conclusions. The enactment of inference objective reflects the preference degree of decision maker to every antecedent component's evaluation. Therefore, it is much fitter for the demands of practical inference.
引用
收藏
页码:247 / 257
页数:11
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