A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis
Author:
Affiliation:
1. Electronics and Computer Science, University of Southampton, Southampton, UK
2. Centre for Risk Research, Southampton Business School, University of Southampton, Southampton, UK
Funder
Horizon 2020 Framework Programme
Southampton Marine and Maritime Institute
Publisher
Informa UK Limited
Subject
Transportation
Link
https://www.tandfonline.com/doi/pdf/10.1080/01441647.2022.2036864
Reference100 articles.
1. The value of meteorological data in marine risk assessment
2. Allianz. (2012). Safety and shipping 1912–2012: From Titanic to Costa Concordia [online]. Accessed 18th May 2020. https://www.agcs.allianz.com/content/dam/onemarketing/agcs/agcs/reports/AGCS-Safety-Shipping-Review-2012.pdf
3. Reliability and validity of risk analysis
4. Marine transportation risk assessment using Bayesian Network: Application to Arctic waters
5. Pattern development for vessel accidents: a comparison of statistical and neural computing techniques
Cited by 46 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A data-driven Ship Risk Profile model for Turkish Straits (TS-SRP) using Machine Learning;Ocean Engineering;2024-11
2. Maritime accident risk prediction integrating weather data using machine learning;Transportation Research Part D: Transport and Environment;2024-11
3. Intelligent ship collision avoidance in maritime field: A bibliometric and systematic review;Expert Systems with Applications;2024-10
4. A marine accident analysis based on data-driven Bayesian network considering weather conditions and its application to Taiwanese waters;Ocean Engineering;2024-10
5. Hazard identification and risk analysis of maritime autonomous surface ships: A systematic review and future directions;Ocean Engineering;2024-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3