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

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Complexity Pub Date : 2024-06-25 DOI:10.1155/2024/4998195
Jun Ma, Yang Wang, Liguang Wang, Luhui Xu, Jiong Zhao
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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.

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构建用于船舶碰撞事故分析的事件图,改善海上交通安全
目前,分析船舶碰撞事故原因的方法主要有三种:统计分析法、事故成因模型法和知识图谱法。随着研究的深入,分析方法更加注重事故各因素之间的客观关联性,得到的分析结果也更加客观准确。在此基础上,本文提出了一种基于船舶碰撞事故事件图(SCAEG)构建的船舶碰撞事故中不同原因和事故传导路径的贡献度分析方法。首先,基于基础理论构建本体。其次,在微调 UIE 模型后提取事件和关系。第三,在事件核心参照解析后构建 SCAEG。最后,本研究基于 SCAEG 进行贡献度分析、事故传导路径分析和事故空间分布分析。该方法的优点如下(i)可以构建更完整、更准确的本体;(ii)采用这种方法可以统一各种信息提取任务,并在小样本标注数据的基础上取得良好效果;(iii)利用这种方法,我们可以进行不同原因的贡献度分析、事故传导路径分析和空间分布分析。实验证明了该方法的有效性。实验得出的分析结果可为相关部门提供辅助决策,减少船舶碰撞事故的发生,提高海上交通安全。
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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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