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

作者:

Highlights:

• The feature correlation in proposed approximate belief rules is handled by discounted weights.

• Expert knowledge can be introduced into the proposed ABRB more easily.

• The key components of the proposed ABRB can be well extended.

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.

论文关键词:Belief rule base,Expert systems,Interpretability,Complex system modelling

论文评审过程:Received 5 July 2020, Revised 18 February 2021, Accepted 16 March 2021, Available online 24 March 2021, Version of Record 24 September 2021.

论文官网地址:https://doi.org/10.1016/j.dss.2021.113558