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Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review

  • Published:2024-03 Issue: Volume:183 Page:103426
  • ISSN:1366-5545
  • Container-title:Transportation Research Part E: Logistics and Transportation Review
  • language:en
  • Short-container-title:Transportation Research Part E: Logistics and Transportation Review

Author:

Yang Ying,Liu Yang,Li Guorong,Zhang Zekun,Liu Yanbin

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

National Key Research and Development Program of China

Shanghai Science International Cooperation Project

Publisher

Elsevier BV

Reference128 articles.

1. Green approaches at sea – The benefits of adjusting speed instead of anchoring;Andersson;Transportation Research Part d: Transport and Environment,2017

2. Dynamic route planning in the Baltic Sea Region – A cost-benefit analysis based on AIS data;Andersson;Maritime Economics & Logistics,2017

3. AIS Data Vulnerability Indicated by a Spoofing Case-Study;Androjna;Applied Sciences,2021

4. Maritime traffic networks: From historical positioning data to unsupervised maritime traffic monitoring;Arguedas;IEEE Transactions on Intelligent Transportation Systems,2018

5. Review of ship energy efficiency;Barreiro;Ocean Engineering,2022

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