Comparative study of statistical and machine learning methods for streetcar incident duration analysis
10.1080/13588265.2022.2131262
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2024
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sg-nus-scholar.10635-2471162024-03-04T04:43:36Z Comparative study of statistical and machine learning methods for streetcar incident duration analysis SIYING ZHU CIVIL AND ENVIRONMENTAL ENGINEERING 10.1080/13588265.2022.2131262 International Journal of Crashworthiness 29 1 16-21 2024-02-14T07:04:27Z 2024-02-14T07:04:27Z 2022-10-06 Article SIYING ZHU (2022-10-06). Comparative study of statistical and machine learning methods for streetcar incident duration analysis. International Journal of Crashworthiness 29 (1) : 16-21. ScholarBank@NUS Repository. https://doi.org/10.1080/13588265.2022.2131262 1358-8265 https://scholarbank.nus.edu.sg/handle/10635/247116 Taylor & Francis Taylor & Francis |
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10.1080/13588265.2022.2131262 |
author2 |
CIVIL AND ENVIRONMENTAL ENGINEERING |
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CIVIL AND ENVIRONMENTAL ENGINEERING SIYING ZHU |
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Article |
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SIYING ZHU |
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SIYING ZHU Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
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SIYING ZHU |
title |
Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
title_short |
Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
title_full |
Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
title_fullStr |
Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
title_full_unstemmed |
Comparative study of statistical and machine learning methods for streetcar incident duration analysis |
title_sort |
comparative study of statistical and machine learning methods for streetcar incident duration analysis |
publisher |
Taylor & Francis |
publishDate |
2024 |
url |
https://scholarbank.nus.edu.sg/handle/10635/247116 |
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