Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Risk Analysis of Pirate Attacks on Southeast Asian Ships Based on Bayesian Networks

Chen, Q, Zhang, J, Gao, J, Lau, YY, Liu, J, Poo, MCP and Zhang, P (2024) Risk Analysis of Pirate Attacks on Southeast Asian Ships Based on Bayesian Networks. Journal of Marine Science and Engineering, 12 (7).

[img]
Preview
Text
Risk Analysis of Pirate Attacks on Southeast Asian Ships Based on Bayesian Networks.pdf - Published Version
Available under License Creative Commons Attribution.

Download (3MB) | Preview

Abstract

As a bridge for international trade, maritime transportation security is crucial to the global economy. Southeast Asian waters have become a high-incidence area of global piracy attacks due to geographic location and complex security situations, posing a great threat to the development of the Maritime Silk Road. In this study, the factors affecting the risk of pirate attacks are analyzed in depth by using the Global Ship Piracy Attacks Report from the IMO Global Integrated Shipping Information System (GISIS) database (i.e., 2013–2022) in conjunction with a Bayesian Network (BN) model, and the Expectation Maximization algorithm is used to train the model parameters. The results show that piracy behaviors and the ship’s risk are the key factors affecting the risk of pirate attacks, and suggestions are made to reduce the risk of pirate attacks. This study develops a theoretical basis for preventing and controlling the risk of pirate attacks on ships, which helps maintain the safety of ship operations.

Item Type: Article
Uncontrolled Keywords: 0405 Oceanography; 0704 Fisheries Sciences; 0911 Maritime Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions: Engineering
Publisher: MDPI
SWORD Depositor: A Symplectic
Date Deposited: 09 Aug 2024 15:55
Last Modified: 09 Aug 2024 16:00
DOI or ID number: 10.3390/jmse12071088
URI: https://researchonline.ljmu.ac.uk/id/eprint/23919
View Item View Item