Failure rate prediction based on AR model and residual correction

Abstract

Based on the study of advantages and disadvantages of the traditional AR model (autoregressive model) and the characteristics of failure rate prediction, an AR model based on neural network residual correction is proposed in this paper. The basic idea is to establish the AR model first to obtain the residual sequence, and next construct the neural network residual prediction model using the residual sequence, and then correct the predicted value of the original AR model using the residual value predicted by the model. The combined model is used to predict the failure rate of a kind of Boeing aircraft. It is proved that this model is suitable for short-term failure rate prediction, and the accuracy of the prediction results is better than that of the single AR model.