A machine learning-based data-driven method for risk analysis of marine accidents-Reference-Cited by-同舟云学术

A machine learning-based data-driven method for risk analysis of marine accidents

Published:2024-06-19 Issue: Volume: Page:1-12
ISSN:2046-4177
Container-title:Journal of Marine Engineering & Technology
language:en
Short-container-title:Journal of Marine Engineering & Technology

Author:

Feng Yinwei¹²^ORCID,Wang Huanxin¹²³⁴^ORCID,Xia Guoqing¹⁴,Cao Wenjie¹⁴,Li Tianyi¹⁴,Wang Xinjian¹²³⁴^ORCID,Liu Zhengjiang¹⁴

Affiliation:

1. Navigation College, Dalian Maritime University, Dalian, People’s Republic of China

2. Liverpool Logistics, Offshore and Marine (LOOM) Research Institute, Liverpool John Moores University, Liverpool, UK

3. Key Laboratory of International Shipping Development and Property Digitization of Hainan Free Trade Port, Hainan Vocational University of Science and Technology, Haikou, People’s Republic of China

4. Key Laboratory of Navigation Safety Guarantee of Liaoning Province, Dalian, People’s Republic of China

Funder

National Natural Science Foundation of China

Bolian Research Funds of Dalian Maritime University

EU H2020 ERC Consolidator Grant program

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/20464177.2024.2368914

Reference50 articles.

1. AGCS. 2023. Safety and shipping review 2023. Allianz Global Corporate & Specialty, Munich, Germany.

2. An analysis of severity of oil spill caused by vessel accidents

3. Investigation of tugboat accidents severity: An application of association rule mining algorithms

4. Analysis of factors affecting the severity of marine accidents using a data-driven Bayesian network

5. Research in marine accidents: A bibliometric analysis, systematic review and future directions

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