An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case
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DOI: 10.1177/1748006X13508107
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Cited by:
- Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
- Jiang, Yonglei & Lu, Jing & Cai, Yutong & Zeng, Qingcheng, 2018. "Analysis of the impacts of different modes of governance on inland waterway transport development on the Pearl River: The Yangtze River Mode vs. the Pearl River Mode," Journal of Transport Geography, Elsevier, vol. 71(C), pages 235-252.
- Gino J. Lim & Jaeyoung Cho & Selim Bora & Taofeek Biobaku & Hamid Parsaei, 2018. "Models and computational algorithms for maritime risk analysis: a review," Annals of Operations Research, Springer, vol. 271(2), pages 765-786, December.
- Daozheng Huang & Gang Zhao, 2019. "A Shared Container Transportation Mode in the Yangtze River," Sustainability, MDPI, vol. 11(10), pages 1-12, May.
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Keywords
Traffic congestion; maritime risk; correlation analysis; Bayesian network; Yangtze River;All these keywords.
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