Train performance analysis using heterogeneous statistical models
This study investigated the eect of harsh winter climate on the performance of high speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance in order to take the time-varying risks of train delays into cons...
Published in: | Atmosphere |
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Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Umeå universitet, Institutionen för matematik och matematisk statistik
2021
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Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-186523 https://doi.org/10.3390/atmos12091115 |
Summary: | This study investigated the eect of harsh winter climate on the performance of high speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance in order to take the time-varying risks of train delays into consideration. Specically, stratied Cox model and heterogeneous Markov chain model were used for modelling primary delays and arrival delays, respectively. Our results showed that the weather variables including temperature, humidity, snow depth, and ice/snow precipitation have signicant impact on the train performance. Special issue, also published as printed edition: Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales / [ed] Ankit Agarwal, Naiming Yuan, Kevin K.W. Cheung and Roopam Shukla. ISBN 978-3-0365-2953-0 (Hbk); ISBN 978-3-0365-2952-3 (PDF); DOI 10.3390/books978-3-0365-2952-3 NoICE |
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