System reliability prediction model based on evidential reasoning algorithm with nonlinear optimization

In this paper, a novel reliability prediction technique based on the evidential reasoning (ER) algorithm is developed and applied to forecast reliability in turbocharger engine systems. The focus of this study is to examine the feasibility and validity of the ER algorithm in systems reliability prediction by comparing it with some existing approaches. To determine the parameters of the proposed model accurately, some nonlinear optimization models are investigated to search for the optimal parameters of forecasting model by minimizing the mean square error (MSE) criterion. Finally, a numerical example is provided to demonstrate the detailed implementation procedures. The experimental results show that the prediction performance of the ER-based prediction model outperforms several existing methods in terms of prediction accuracy or speed.