On the Interpretability of Belief Rule-Based Expert Systems

被引:81
|
作者
Cao, You [1 ]
Zhou, Zhijie [1 ,2 ]
Hu, Changhua [1 ]
He, Wei [3 ]
Tang, Shuaiwen [1 ]
机构
[1] High Tech Inst Xian, Xian 710025, Peoples R China
[2] Xian Univ Technol, Dept Informat & Control Engn, Xian 710048, Peoples R China
[3] Harbin Normal Univ, Sch Comp Sci & Informat Engn, Harbin 150025, Peoples R China
关键词
Cognition; Optimization; Uncertainty; Artificial neural networks; Support vector machines; Fuzzy systems; Guidelines; Belief rule base; expert knowledge; interpretability; optimization; EVIDENTIAL REASONING APPROACH; DECISION-ANALYSIS; INFERENCE; METHODOLOGY; CONSTRAINTS;
D O I
10.1109/TFUZZ.2020.3024024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the generalization of fuzzy systems, the belief rule base (BRB) expert system is transparent and interpretable. However, the interpretability of BRB has almost been ignored recently and leads to the decrease of model credibility. The main reason is the lack of unified guidelines for establishing an interpretable BRB expert system. In this article, the interpretability characteristics of BRB are summarized systematically, which can be used as the guideline of BRB establishment. Four interpretability criteria are proposed to ensure the interpretability of BRB in the optimization. A modified optimization algorithm with the interpretability constraints transformed from the interpretability criteria is further developed. As such, an interpretable BRB can be established. A case study for health state evaluation of the aerospace relay is conducted to verify the effectiveness of the proposed method.
引用
收藏
页码:3489 / 3503
页数:15
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