Li, T, Wang, X, Zhang, Z and Feng, Y (2025) A novel feature engineering method for severity prediction of marine accidents. Journal of Marine Engineering & Technology. ISSN 2046-4177

Text A novel feature engineering method for severity prediction of marine accidents.pdf - Accepted Version Restricted to Repository staff only until 27 February 2026. Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (935kB)

Abstract

Predicting the severity of marine accidents is a crucial issue in the field of maritime safety. To enhance the accuracy of predicting marine accident severity, this study proposes a three-stage feature engineering approach called Integrated Feature Engineering and Balancing (IFEB). In the first stage, a method called Association Rule Fusion is developed to simplify multiple interrelated risk influential factors into a composite factor. In the second stage, the Support Vector Machine Synthetic Minority Over-sampling Technique is employed to address the issue of class imbalance. In the third stage, a predictive model-based feature selection method is utilised to identify features that positively influence the predictive model. Subsequently, various advanced machine learning models are employed to predict the output of IFEB, and the optimal predictor is selected. Finally, a series of ablation studies are conducted to validate the contributions of each module within IFEB to the overall model performance. The research findings indicate that IFEB can improve the average performance of each predictive model by up to 6.43%, IFEB combined with Light Gradient Boosting Machine emerges as the most stable and effective predictive model. This study provides an effective predictive tool for enhancing maritime safety and reducing the risk of marine accidents.

Item Type:	Article
Additional Information:	This is an Accepted Manuscript version of the following article, accepted for publication in Journal of Marine Engineering & Technology. Li, T., Wang, X., Zhang, Z., & Feng, Y. (2025). A novel feature engineering method for severity prediction of marine accidents. Journal of Marine Engineering & Technology, 1–16. https://doi.org/10.1080/20464177.2025.2469336. It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (Deed - Attribution-NonCommercial-NoDerivatives 4.0 International - Creative Commons ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Uncontrolled Keywords:	4007 Control Engineering, Mechatronics and Robotics; 40 Engineering; 4015 Maritime Engineering; Machine Learning and Artificial Intelligence; 4007 Control engineering, mechatronics and robotics; 4015 Maritime engineering; 4602 Artificial intelligence
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Engineering
Publisher:	Taylor and Francis Group
SWORD Depositor:	A Symplectic
Date Deposited:	02 Apr 2025 09:55
Last Modified:	02 Apr 2025 10:00
DOI or ID number:	10.1080/20464177.2025.2469336
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26064

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