The Prediction of Delay Time Class Caused by CTCS-3 Onboard System Fault Based on Decision Tree

Abstract

The faults of train control system will lead to delay, which will affect the operational efficiency of the railway network. In this paper, the decision tree algorithm (CART) is used to predict the delay time level caused by CTCS-3 On-board System Fault, which takes the location of train failure, the fault component of CTCS-3 on-board system, the fault phenomenon of CTCS-3 on-board system as data features. In the natural language fault record, based on expert experience, extract the key features needed and grade the delay time. The selected features are put into the decision tree algorithm for classification and prediction, SMOTE algorithm is used to solve the problem of unbalanced number of categories, and grid search algorithm is used to adjust the model parameters. Finally, the output results of the algorithm are analyzed. The decision tree model yields a classification accuracy of 76% for the given data of fault feature and can be considered for delay time level prediction caused by CTCS-3 system fault. From the experimental results, the proposed method can be recommended for the prediction of the delay time level caused by CTCS-3 system fault.