A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis
Author
Abstract
Suggested Citation
DOI: 10.1080/01441647.2022.2036864
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Ejder, Emir & Dinçer, Samet & Arslanoglu, Yasin, 2024. "Decarbonization strategies in the maritime industry: An analysis of dual-fuel engine performance and the carbon intensity indicator," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
- Yang, Ying & Liu, Yang & Li, Guorong & Zhang, Zekun & Liu, Yanbin, 2024. "Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
- Ankur Tayal & Saurabh Agrawal & Rajan Yadav, 2024. "Implementation of industry 4.0 in construction industry: a review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(9), pages 4163-4182, September.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:transr:v:43:y:2023:i:1:p:108-130. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TTRV20 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.