Zeitschriftenartikel:
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;
S. 45
- 47.
Kurzfassung englisch:
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.
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.11128/sne.29.sn.10467
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.