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Modelling ship collision risk based on the statistical analysis of historical data: A case study in Hong Kong waters

Wang, YF, Wang, LT, Jiang, JC, Wang, J and Yang, ZL (2020) Modelling ship collision risk based on the statistical analysis of historical data: A case study in Hong Kong waters. Ocean Engineering, 197. ISSN 0029-8018

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Abstract

Collision, as a common type of ship accidents, leads to serious property loss and personal injury. In this paper, a new framework of quantitative risk assessment is proposed by quantifying the probability and the corresponding consequence based on the historical accident data. Firstly, the consequences of ship collisions are quantified and classified using an equivalent consequence method. Secondly, a decision tree model is established to analyse the impact of ship attributes on the collision consequences. The main ship attributes contributing to collision are determined, based on which, a BP neural network model is developed to estimate the probabilities of the different consequences. Thirdly, the collision risk is predicted by integrating the collision probabilities with the corresponding consequences. Fourthly, a case study in Hong Kong waters is investigated and the results are compared with the available references to validate the proposed framework. The new model can be used to assess present risks to plan preventive measures for the potential collision accidents. © 2019

Item Type: Article
Uncontrolled Keywords: 0905 Civil Engineering, 0911 Maritime Engineering, 0405 Oceanography
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions: Maritime & Mechanical Engineering
Publisher: Elsevier
Date Deposited: 26 Feb 2020 10:40
Last Modified: 26 Feb 2020 10:40
DOI or Identification number: 10.1016/j.oceaneng.2019.106869
URI: http://researchonline.ljmu.ac.uk/id/eprint/12316

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