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A risk assessment approach to improve the resilience of a seaport system using Bayesian networks

John, A and Yang, Z and Riahi, R and Wang, J (2016) A risk assessment approach to improve the resilience of a seaport system using Bayesian networks. OCEAN ENGINEERING, 111. pp. 136-147. ISSN 0029-8018

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Abstract

Over the years, many efforts have been focused on developing methods to design seaport systems, yet disruption still occur because of various human, technical and random natural events. Much of the available data to design these systems are highly uncertain and difficult to obtain due to the number of events with vague and imprecise parameters that need to be modelled. A systematic approach that handles both quantitative and qualitative data, as well as means of updating existing information when new knowledge becomes available is required. Resilience, which is the ability of complex systems to recover quickly after severe disruptions, has been recognised as an important characteristic of maritime operations. This paper presents a modelling approach that employs Bayesian belief networks to model various influencing variables in a seaport system. The use of Bayesian belief networks allows the influencing variables to be represented in a hierarchical structure for collaborative design and modelling of the system. Fuzzy Analytical Hierarchy Process (FAHP) is utilised to evaluate the relative influence of each influencing variable. It is envisaged that the proposed methodology could provide safety analysts with a flexible tool to implement strategies that would contribute to the resilience of maritime systems.

Item Type: Article
Uncontrolled Keywords: 0905 Civil Engineering, 0911 Maritime Engineering
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Maritime and Mechanical Engineering
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Related URLs:
Date Deposited: 16 Mar 2016 11:08
Last Modified: 19 Nov 2016 00:50
DOI or Identification number: 10.1016/j.oceaneng.2015.10.048
URI: http://researchonline.ljmu.ac.uk/id/eprint/3250

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