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

  • Lijuan ShiEmail author
  • Ang Li
  • Liquan Chen
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 617)


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.


CTCS-3 on-board system fault Delay time class Expert knowledge Decision tree 



Authors would like to acknowledge the support of the research program of Comprehensive Support Technology for Railway Network Operation (2018YFB1201403), which is a subproject of Advanced Railway Transportation Special Project belonging to the 13th Five-Year National Key Research and Development Plan funded by Ministry of Science and Technology of China.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Shanghai Key Laboratory of Rail Infrastructure Durability and System SafetyTongji UniversityJiading District, ShanghaiPeople’s Republic of China
  2. 2.Key Laboratory of Road and Traffic Engineering of Ministry of EducationTongji UniversityJiading District, ShanghaiPeople’s Republic of China
  3. 3.China Railway Guangzhou Group Co., Ltd.GuangzhouChina

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