Title: Bayesian network to predict environmental risk of a possible ship accident

Authors: Zoe S. Nivolianitou; Ioanna A. Koromila; Theodoros Giannakopoulos

Addresses: Institute of Nuclear Technology and Radiation Protection, NCSR 'Demokritos', Aghia Paraskevi, 15310, Greece ' Institute of Nuclear Technology and Radiation Protection, NCSR 'Demokritos', Aghia Paraskevi, 15310, Greece ' Institute of Informatics and Telecommunications, NCSR 'Demokritos', Aghia Paraskevi, 15310, Greece

Abstract: This paper presents a probabilistic model predicting the risk of a possible ship accident occurrence in the Aegean Sea. Two types of accident scenarios (collision and grounding) have been studied using the Bayesian networks methodology. The model takes into account the static information of the vessel, namely the vessel type, size, age and flag. The training of the network was performed using the data of the historical accident database of the Marine Rescue Coordination Centre. In order to demonstrate the applicability of this method, two sample use cases have been conducted. The whole case study has been run within the framework of the AMINESS project.

Keywords: Bayesian networks; maritime safety; risk assessment; environmental risks; shipping accidents; maritime accidents; risk modelling; Aegean Sea; ship collisions; ship grounding; vessel type; vessel size; vessel age; vessel flag.

DOI: 10.1504/IJRAM.2016.077381

International Journal of Risk Assessment and Management, 2016 Vol.19 No.3, pp.228 - 239

Received: 29 Jan 2015
Accepted: 28 Jul 2015

Published online: 26 Jun 2016 *

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