Concise belief rule base with credibility decay for system performance prediction

In engineering scenarios, the performance of industrial systems varies continuously, making it necessary to develop a prediction model to track system performance . Recently, a modeling approach known as the concise belief rule base (CBRB) has provided an effective reference for performance prediction. However, CBRB ignores the decay phenomenon of information credibility during the prediction process, leading to suboptimal output accuracy. To address this limitation, a novel performance prediction model based on the concise belief rule base with credibility decay (CBRB-CD) is put forward. The proposed model incorporates a decay factor to reflect the property that the credibility of belief rules decays over time. Meanwhile, the decay factor is aggregated into the fusion process of belief rules, from which the prediction results are generated. Furthermore, a stability analysis of the prediction model is carried out by introducing external perturbations to validate the prediction results. The analysis results quantitatively reveal the changing patterns of prediction results under perturbed environments. Finally, real-world experiments on aerospace relays demonstrate the feasibility of the proposed model.