Publication | Closed Access
On the Interpretability of Belief Rule-Based Expert Systems
174
Citations
39
References
2020
Year
Artificial IntelligenceBelief Rule BaseFuzzy SystemsEngineeringFuzzy ModelingDiagnosisIntelligent SystemsFuzzy Risk AnalysisData ScienceBelief FunctionSystems EngineeringFuzzy OptimizationDecision TheoryReliabilityFuzzy LogicExpert SystemsComputer ScienceExpert SystemAerospace EngineeringAutomated ReasoningNeuro-fuzzy SystemFuzzy Expert SystemBelief MergingRule-based SystemEpistemologyInterpretable Brb
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.
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