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Construction of Event Graph for Ship Collision Accident Analysis to Improve Maritime Traffic Safety

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  • Jun Ma
  • Yang Wang
  • Liguang Wang
  • Luhui Xu
  • Jiong Zhao
  • Hiroki Sayama

Abstract

At present, there are three main methods for analyzing the causes of ship collision accidents: statistical analysis, accident causation models, and knowledge graphs. With the deepening of research, the analysis methods pay more attention to the objective correlation between various factors of the accident, and the analysis results obtained are more objective and accurate. On this basis, this paper proposes a method for analyzing the contribution degree of different causes and accident conduction paths in ship collision accidents based on the construction of the Ship Collision Accidents Event Graph (SCAEG). Firstly, the ontology is constructed based on the grounded theory. Secondly, events and relationships are extracted after fine-tuning the UIE model. Thirdly, the SCAEG is constructed after event coreference resolution. Finally, this research conducts the contribution degree analysis, accident conduction path analysis, and accident spatial distribution analysis based on SCAEG. The advantages of this method include the following: (i) it can construct a more complete and accurate ontology; (ii) adopting this approach can unify various information extraction tasks and achieve good results based on small sample annotation data; and (iii) using this method, we can conduct contribution degree analysis of different causes, accident conduction path analysis, and spatial distribution analysis. Experimental evidence demonstrates the effectiveness of this method. The analytical results obtained from the experiments can provide assistant decision-making for relevant departments to reduce the occurrence of ship collision accidents and improve maritime traffic safety.

Suggested Citation

  • Jun Ma & Yang Wang & Liguang Wang & Luhui Xu & Jiong Zhao & Hiroki Sayama, 2024. "Construction of Event Graph for Ship Collision Accident Analysis to Improve Maritime Traffic Safety," Complexity, Hindawi, vol. 2024, pages 1-23, June.
  • Handle: RePEc:hin:complx:4998195
    DOI: 10.1155/2024/4998195
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