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The article discusses the use of interpretable belief rule base (BRB) models in health condition assessment for complex systems. It proposes a new method, called interpretable BRB with reference value optimization (I-BRB), which addresses issues with inaccurate expert-provided parameters and reduced interpretability after model optimization. The method is validated through a case study on bearing components of a flywheel system, showing higher accuracy in health condition assessment.
