A new approximate belief rule base expert system for complex system modelling

被引:61
作者
Cao, You [1 ]
Zhou, Zhi Jie [1 ]
Hu, Chang Hua [1 ]
Tang, Shuai Wen [1 ]
Wang, Jie [1 ]
机构
[1] High Tech Inst Xian, Xian 710025, Shaanxi, Peoples R China
关键词
Belief rule base; Expert systems; Interpretability; Complex system modelling; INFERENCE; METHODOLOGY;
D O I
10.1016/j.dss.2021.113558
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Expert knowledge is the foundation of the interpretability of belief rule base (BRB) expert system. However, the rule explosion problem and weak extendability of BRB limit the utilization of expert knowledge. To solve this problem, a new approximate belief rule with single attributes is proposed, with which a new expert system named as ABRB is constructed. In the new rule, the correlation among attributes is discounted by the independency factor. To illustrate the similar modelling ability of ABRB and BRB, the universal approximation ability of ABRB is proved theoretically. In the proposed ABRB, the key components, such as attributes, referential values, and the frame of discernment, can be extended to guarantee its effectiveness in the long-term practice. A case study of the Lithium-ion power battery is conducted to verify the effectiveness of the proposed model.
引用
收藏
页数:15
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