Application of ARIMA-BP Combined Model in Equipment Failure Rate Prediction
Whether the prediction result of equipment failure rate is accurate or not directly affects the result of equipment maintainability verification test.In order to improve the prediction accuracy of equip-ment failure rate,a new combined model prediction mode is proposed.The time series ARIMA prediction model and BP neural network model are used to predict the equipment failure rate respectively,and then on the basis of the two kinds of single item of model prediction,the error squares and the minimum principle are used to establish the combined prediction model to predict the equipment failure rate.The prediction results show that the combined prediction model can extract the linear and nonlinear characteristics of equipment fail-ure rate data well,and the accuracy of prediction result is higher than that of the two single models.
万方数据
维普
