| Issue |
E3S Web Conf.
Volume 656, 2025
2025 6th International Conference on Urban Engineering and Management Science (ICUEMS 2025)
|
|
|---|---|---|
| Article Number | 01009 | |
| Number of page(s) | 5 | |
| Section | Urban Infrastructure and Safety | |
| DOI | https://doi.org/10.1051/e3sconf/202565601009 | |
| Published online | 30 October 2025 | |
Prediction of the severity of maritime disasters based on a binary probit model
First East China Sea Rescue Flight, Ministry of Transportation and Communications, Shanghai, China
* Corresponding author: chenyanghu2025@163.com
To comprehensively analyze the characteristic factors of maritime accidents in China, this study categorized the attributes and extracted the features of 85 accident reports published by the China Maritime Safety Administration from 2020–2021. A binary probit regression model was used to construct a predictive model for the severity of maritime accidents. The results indicated that the model provides good predictive performance. Factors that significantly influenced the occurrence of severe accidents include the accident month (between January and June), accident type (self-sinking), visibility ≥5 nautical miles, and wind force <level 6.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.