Exploring key factors for long-term vessel incident risk prediction

Factor analysis acts a pivotal role in enhancing maritime safety. Most previous studies conduct factor analysis within the framework of incident-related label prediction, where the developed models can be categorized into short-term and long-term prediction models. The long-term models offer a more strategic approach, enabling more proactive risk management, compared to the short-term ones. Nevertheless, few studies have devoted to rigorously identifying the key factors for the long-term prediction and undertaking comprehensive factor analysis. Hence, this study aims to delve into the key factors for predicting the incident risk levels in the subsequent year given a specific datestamp. The majority of candidate factors potentially contributing to the incident risk are collected from vessels’ historical safety performance data spanning up to five years. An improved embedded feature selection method, which integrates …

Recommended citation: T Chen, H Wang, Y Cai, M Liang, Q Meng. (2025). Exploring key factors for long-term vessel incident risk prediction. Reliability Engineering & System Safety, 253, 110565. https://www.sciencedirect.com/science/article/pii/S0951832024006379