Exploring significant predictors of freight rail intermodal operation delays using causal Machine Learning
Speaker: Juan Pineda-Jaramillo (Faculty of Science, Technology and Medicine; University of Luxembourg)
Title: Exploring significant predictors of freight rail intermodal operation delays using causal Machine Learning
Time: Wednesday, 2021.07.07, 10:00 a.m. (CET)
Place: fully virtual (contact Jakub Lengiewicz to register)
Format: 30 min. presentation + 30 min. discussion
Abstract: Delays in freight rail intermodal operations generate negative impacts on the railway industry, so identifying the causes associated to these delays is vital to mitigate operational risks. In this seminar, we will present a set of Machine Learning models that were trained to predict the delays in freight rail intermodal operations, and then the most suitable model was used to explore the significant predictors which cause those delays, using data from the National Railway Company of Luxembourg that connects Bettembourg with several EU countries.