Volume 43 Issue 2
Apr.  2025
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MA Xiaoxue, ZHANG Ruiwen, QIAO Weiliang, HAN Bing, YANG Jie. An Analysis of the Seafarers' Unsafe Actions Causality Network Based on Association Rule Mining[J]. Journal of Transport Information and Safety, 2025, 43(2): 1-10. doi: 10.3963/j.jssn.1674-4861.2025.02.001
Citation: MA Xiaoxue, ZHANG Ruiwen, QIAO Weiliang, HAN Bing, YANG Jie. An Analysis of the Seafarers' Unsafe Actions Causality Network Based on Association Rule Mining[J]. Journal of Transport Information and Safety, 2025, 43(2): 1-10. doi: 10.3963/j.jssn.1674-4861.2025.02.001

An Analysis of the Seafarers' Unsafe Actions Causality Network Based on Association Rule Mining

doi: 10.3963/j.jssn.1674-4861.2025.02.001
  • Received Date: 2024-09-02
  • Seafarers' unsafe actions are pivotal contributors to the frequent occurrence of waterborne traffic accidents. However, the majority of existing research tends to concentrate on the analysis of single factors, with insufficient exploration of the underlying mechanisms involving the interplay of multiple factors. Based on 886 waterborne traffic accident investigation reports, unsafe actions and its causal factors are extracted by utilizing Grounded Theory. According to the framework of human factor analysis and classification system (HFACS), an analytical framework for the unsafe actions and causal factors is established, encompassing five levels and 76 factors. association rule mining (ARM) algorithm is utilized for the exploration of the coupling relationship and interaction between the seafarers' unsafe actions. It reveals how various causal factors synergistically contribute to the occurrence of seafarers' unsafe actions. By employing complex network theory, the results of association rule analysis are mapped onto a directed weighted network, constructing a causal network model for seafarers' unsafe actions. The key nodes influencing seafarers' unsafe actions are identified by analyzing the topological characteristics of the network. It is highlighted that the causation network of seafarers' unsafe actions exhibits typical small-world network characteristics, with an average clustering coefficient of 0.63 and an average path length of 2.095 2. This indicates that the influencing factors are closely interconnected, making it susceptible to triggering chain reactions. Among the strong association rules, "severe lookout negligence by watchkeeping seafarers" has a 55% probability of interacting with other factors to trigger other seafarers' unsafe actions. The betweenness centrality value of it is approximately 0.262 7, playing a crucial intermediary role in the development of causation pathways. "Failure to adopt a safe speed" and "inadequate use of navigational aids" exhibit a highly correlated relationship in grounding accidents, with a mutual inducement probability of 70% when interacting with other factors. Unsafe actions such as "failure to detect and implement effective risk mitigation measures in a timely manner" and "poor emergency response capabilities of the captain" frequently emerge in the association rules across multiple accident types. It indicates that these unsafe actions occupy a pivotal position in the process of seafarers' risk management.

     

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