Bayesian Network Modelling for Navigation Status Control of Cargo Ships in the Three Gorges Waterway

This paper proposes a Bayesian network-based navigation status control model to estimate the probability of cargo ships being allowed to navigate in the waterway between the Three Gorges Dam and the Gezhouba Dam. The objective of the study is to develop a model to decide the navigation status of cargo ships by considering their attribute characteristics and the navigation risk factors related to the channel flow. Therefore, environmental condition, ship condition, and traffic complexity three modules are comprehensively considered in the proposed model. Specifically, the historical navigation data of cargo ships collected from the Three Gorges Navigation Administration, together with the navigation regulations of this waterway, are used to analyze the influencing factors of the navigation status and to construct the graphical structure of the Bayesian network. Moreover, the conditional probabilities of some nodes are determined using the Noisy-OR gate and the IF-THEN method. Finally, the navigation records are used to verify the feasibility of the navigation status control model for cargo ships, and the estimated average navigable probability of cargo ships is 89%. The results indicate that the proposed model can reasonably estimate the navigation probability of cargo ships and assist maritime supervisors in controlling the navigation of cargo ships in the Three Gorges Waterway.

• Record URL:
  • https://doi.org/10.1016/j.ress.2024.110018
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0951832024000930
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09518320
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Xu, Xueqian
  • Wu, Bing
  • Man, Jie
  • Guedes Soares, C
  • 0000-0002-8570-4263
• Publication Date: 2024-5

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 110018
• Serial:
  • Reliability Engineering & System Safety
  • Volume: 245
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0951-8320
  • Serial URL: https://www.sciencedirect.com/journal/reliability-engineering-and-system-safety

Subject/Index Terms

• TRT Terms: Bayes' theorem; Cargo ships; Inland waterways; Maritime safety; Ship pilotage; Streamflow
• Identifier Terms: Gezhouba Dam; Three Gorges Dam
• Geographic Terms: Yangtze River
• Subject Areas: Freight Transportation; Hydraulics and Hydrology; Marine Transportation; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01914151
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 10 2024 5:15PM