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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7




ISSN 2083-6473
ISSN 2083-6481 (electronic version)




Associate Editor
Prof. Tomasz Neumann

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
An Expert Elicitation Analysis for Vessel Allision Risk Near the Offshore Wind Farm by Using Fuzzy Rule-Based Bayesian Network
Q. Yu 1 , K. Liu 1
1 Wuhan University of Technology, Wuhan, China
ABSTRACT: This paper develops an expert based framework for analysing and synthesising the ship allision risk near the offshore wind farm (OWF) on the basis of a generic Fuzzy Bayesian network and FMEA analysis. This framework is specifically intended to overcome the difficulty of using traditional risk assessment methods in OWF allision. Under the introduced framework, subjective belief degrees are assigned to model the incompleteness encountered in establishing the knowledge base. The fuzzy transformation technology is then used to introduce all judgements results under various situations. Fully, a Bayesian network is established to aggregate all relevant attributes to the conclusion and to prioritise potential allision risk level of each ship categories. A series of case studies of different ship categories are studied to illustrate the application of the proposed framework. Results show that the fishing vessel and the service vessel have a higher allision risk than the merchant vessel due to insufficient risk detection. The collision consequence of the tanker is significantly higher than other types of vessel. The framework facilitates subjective risk assessment when historical failure data is not available in their practice, which provides support to OWF-safeguarding and decision-making.
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Citation note:
Yu Q., Liu K.: An Expert Elicitation Analysis for Vessel Allision Risk Near the Offshore Wind Farm by Using Fuzzy Rule-Based Bayesian Network. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 13, No. 4, doi:10.12716/1001.13.04.16, pp. 831-837, 2019

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