Data-Driven Analysis of the Causal Chain of Waterborne Traffic Accidents: A Hybrid Framework Based on an Improved Human Factors Analysis and Classification System with a Bayesian Network

Data-Driven Analysis of the Causal Chain of Waterborne Traffic Accidents: A Hybrid Framework Based on an Improved Human Factors Analysis and Classification System with a Bayesian Network

In the context of economic globalization, waterborne transportation plays an important role in international trade and logistics. However, waterborne traffic accidents pose a severe threat to life, property safety, and the environment. To gain a deeper understanding of the causal mechanisms behind w...

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Bibliographic Details
Main Authors: Xiangyu Yin, Yan Yan, Jiahao Wang, Hongzhuan Zhao, Qingyan Wu, Qi Xu
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Journal of Marine Science and Engineering
Subjects:
waterborne traffic accidents
causal chain analysis
HFACS
Bayesian network
data-driven analysis
Online Access:https://www.mdpi.com/2077-1312/13/3/393
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