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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Bibliographic Details
Published in:Atmosphere
Main Authors: Jianfeng Wang, Jun Yu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/atmos12091115
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spelling 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
collection 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
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