Weighted fuzzy reasoning using weighted fuzzy Petri nets

被引：83
|
作者：
Chen, SM [1 ]
机构：
[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan
来源：
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 2002年 / 14卷 / 02期
关键词：
fuzzy production rules; fuzzy numbers; knowledge base; rule-based systems; weighted fuzzy reasoning; Weighted Fuzzy Petri Nets;
D O I：
10.1109/69.991723
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a Weighted Fuzzy Petri Net model (WFPN) and proposes a weighted fuzzy reasoning algorithm for rule-based systems based on Weighted Fuzzy Petri Nets. The fuzzy production rules in the knowledge base of a rule-based system are modeled by Weighted Fuzzy Petri Nets, where the truth values of the propositions appearing in the fuzzy production rules and the certainty factors of the rules are represented by fuzzy numbers. Furthermore, the weights of the propositions appearing in the rules are also represented by fuzzy numbers, The proposed weighted fuzzy reasoning algorithm can allow the rule-based systems to perform fuzzy reasoning in a more flexible and more intelligent manner.
引用
收藏
页码：386 / 397
页数：12
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