An interval construction belief rule base with interpretability for complex systems

He, Wei; Cheng, Xiaoyu; Zhao, Xu; Zhou, Guohui; Zhu, Hailong; Zhao, Erkai; Qian, Guangyu

doi:10.1016/j.eswa.2023.120485

Cited by 16 publications

(3 citation statements)

References 32 publications

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“…The method can guarantee interpretability and accuracy at the same time. As a result, the hybrid model excels in addressing a wide range of diverse problems and complex data distributions [9]. For example, belief rule base expert systems, fuzzy expert systems and fuzzy neural networks.…”

Section: Introductionmentioning

confidence: 99%

An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base

2024

KSII TIIS

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Section: Introductionmentioning

confidence: 99%

An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base

2024

KSII TIIS

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“…However, expert knowledge is not sufficient to build an accurate health status assessment method based on the BRB [34]. In addition, the health status assessment methods of spacecraft flywheel systems, which are a type of precision aerospace equipment, require interpretability [35]. The above three problems in real systems pose challenges to health status assessment.…”

Section: Introductionmentioning

confidence: 99%

An interpretable spacecraft flywheel system health status assessment method under perturbation

Zhang,

He,

et al. 2024

Meas. Sci. Technol.

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Health status assessment is an important measure for maintaining the safety of spacecraft flywheel systems. The influence of noise, sensor quality, and other disturbance factors can lead to a decrease in the reliability of the collected information. This can affect the model accuracy. Moreover, a loss of belief in the model is frequently caused by the opaque nature of the procedure and the incomprehensibility of the outcomes, particularly in fields such as aerospace. It is urgent to maintain the interpretability of the model and successfully identify the unreliability of the observed data. Therefore, this paper proposes a spacecraft flywheel system health status assessment method under perturbation based on interpretable belief rule base with attribute reliability (IBRB-r). First, the attribute reliability is calculated based on the average distance method, and a new fusion method of attribute reliability is proposed to reduce the interference of unreliable information. Then, a new interpretable constraint strategy is proposed to improve the rationality and interpretability of the parameters. Finally, the proposed method is validated by a case study of the health status assessment of a spacecraft flywheel system. Experiments show that the IBRB-r maintains high accuracy and interpretability under unreliable observation data.

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“…While data‐driven methods can provide accurate estimation based on available data, they often lack interpretability and transparency. These models lack insight into the internal structure and mechanism of Li‐ion batteries, and the estimation process may not be easily traceable 13 …”

Section: Introductionmentioning

confidence: 99%

A new state‐of‐health estimation method for Li‐ion batteries based on interpretable belief rule base with expert knowledge credibility

Yin,

Jia,

et al. 2023

Energy Science & Engineering

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State‐of‐health (SOH) estimation methods for Li‐ion batteries are important for the safe operation of the entire system. However, it is often challenging due to the uncertainty within the batteries and the criteria for model interpretability. Belief rule base (BRB) is a rule‐based expert system that has certain advantages for both aspects. However, several problems with BRB interpretability need to be solved urgently. First, expert knowledge credibility is often given subjectively, while objective information is neglected to be considered. Second, BRB interpretability is easily ignored or corrupted in the optimization process. Third, expert knowledge is assumed to be completely reliable information to be used as interpretability evaluation criterion. Therefore, a new SOH estimation method for Li‐ion batteries based on interpretable BRB with expert knowledge credibility (IBRB‐c) is proposed. In the IBRB‐c, the calculation method of expert knowledge credibility is given. Then, an optimization algorithm with interpretability strategies is used. Finally, the concept of the fuzzy interpretable interval is proposed to design the interpretable evaluation criterion. The effectiveness of the proposed method is verified by using the experiment of NASA Li‐ion battery as a case study.

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An interval construction belief rule base with interpretability for complex systems

Cited by 16 publications

References 32 publications

An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base

An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base

An interpretable spacecraft flywheel system health status assessment method under perturbation

A new state‐of‐health estimation method for Li‐ion batteries based on interpretable belief rule base with expert knowledge credibility

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