Train Performance Analysis Using Heterogeneous Statistical Models
This study investigated the effect of a 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 to take time-varying risks of train delays into consideration...
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Online Access: | https://doi.org/10.3390/atmos12091115 |
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ftmdpi:oai:mdpi.com:/2073-4433/12/9/1115/ 2023-08-20T04:08:46+02:00 Train Performance Analysis Using Heterogeneous Statistical Models Jianfeng Wang Jun Yu agris 2021-08-30 application/pdf https://doi.org/10.3390/atmos12091115 EN eng Multidisciplinary Digital Publishing Institute Climatology https://dx.doi.org/10.3390/atmos12091115 https://creativecommons.org/licenses/by/4.0/ Atmosphere; Volume 12; Issue 9; Pages: 1115 stratified Cox model heterogeneous Markov chain model likelihood ratio test primary delay arrival delay Text 2021 ftmdpi https://doi.org/10.3390/atmos12091115 2023-08-01T02:34:30Z This study investigated the effect of a 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 to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance. Text Northern Sweden MDPI Open Access Publishing Atmosphere 12 9 1115 |
institution |
Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
stratified Cox model heterogeneous Markov chain model likelihood ratio test primary delay arrival delay |
spellingShingle |
stratified Cox model heterogeneous Markov chain model likelihood ratio test primary delay arrival delay Jianfeng Wang Jun Yu Train Performance Analysis Using Heterogeneous Statistical Models |
topic_facet |
stratified Cox model heterogeneous Markov chain model likelihood ratio test primary delay arrival delay |
description |
This study investigated the effect of a 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 to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance. |
format |
Text |
author |
Jianfeng Wang Jun Yu |
author_facet |
Jianfeng Wang Jun Yu |
author_sort |
Jianfeng Wang |
title |
Train Performance Analysis Using Heterogeneous Statistical Models |
title_short |
Train Performance Analysis Using Heterogeneous Statistical Models |
title_full |
Train Performance Analysis Using Heterogeneous Statistical Models |
title_fullStr |
Train Performance Analysis Using Heterogeneous Statistical Models |
title_full_unstemmed |
Train Performance Analysis Using Heterogeneous Statistical Models |
title_sort |
train performance analysis using heterogeneous statistical models |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/atmos12091115 |
op_coverage |
agris |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_source |
Atmosphere; Volume 12; Issue 9; Pages: 1115 |
op_relation |
Climatology https://dx.doi.org/10.3390/atmos12091115 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/atmos12091115 |
container_title |
Atmosphere |
container_volume |
12 |
container_issue |
9 |
container_start_page |
1115 |
_version_ |
1774721250000633856 |