P. Y. Boyko, E. M. Bikov, E. I. Sokolov, D. A. Yarotsky, “Application of Machine Learning to Incident Ranking at Moscow Railway”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2017, Issue 2,Pages <nobr>43

DATA ANALYSIS

Application of Machine Learning to Incident Ranking at Moscow Railway

P. Y. Boyko^a, E. M. Bikov^b, E. I. Sokolov^c, D. A. Yarotsky^a

^a Skolkovo Institute of Science and Technology
^b Institute for Information Transmission Problems (IITP)
^c Technical Center for Automation and Remote control at OJSC "Russian Railways"

Abstract: Moscow Railway, a large railway network including 8800 kilometers of track and 549 stations, is equipped with tens of thousands of devices for automatic registration of system failures. Alerts produced by these devices are processed by operators of the Infrastructure Management Center. The alert flow is very intense and creates a significant stress on the operators while about 97

Keywords: railroad monitoring, incident ranking, machine learning, feature engineering, ensemble of decision trees, XGBoost.