Publications in Scientific Journals:

D. Leser, M. Wastian, M. Rößler, M. Landsiedl, E. Hajrizi:
"Comparison of Prediction Models for Delays of Freight Trains by Using Data Mining and Machine Learning Methods";
Simulation Notes Europe, 29 (2019), 1; 45 - 47.

English abstract:
On the one hand, having a tight schedule is desirable and very cost-efficient for freight transport companies. On the other hand, a tight schedule increases the impact of delays and cancellations. Furthermore, the prediction of delays is extremely complex, because they depend on many factors of influence. To address these issues, this work will show an approach to forecast delays of freight trains by using data mining and machine learning methods.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.