Knowledge Modeling and Analysis for Railway Fire Accident Using Ontology-Based Knowledge Graph

Abstract

AbstractAs a typical scene of railway accidents, railway fire hazard will lead to heavy losses and serious social impact once it happens. However, there are many factors causing the disaster of railway fire and the coupling relationship among the factors is complicated. Therefore, an ontology-based knowledge graph construction and analysis method is proposed. First, based on FAR accident data of American railways, the construction method of railway accident ontology and its relationship is studied, and the pattern layer of railway accident knowledge graph is established. Second, the correlation and importance analysis methods of railway fire accidents are studied, combining with the causative mechanism of fire accidents, a multi-dimensional fusion model is established to extract the fire entities. Third, Neo4j is used to construct the knowledge graph of railway fire accidents. Finally, the railway fire accident knowledge graph constructed in this paper is applied and verified to realize the accurate positioning of the key factors of railway fire accidents and the accurate query of their paths, which is of great significance for the identification, prevention and control of the key risk points and risk paths of railway fire accidents. The construction and application of this knowledge graph will provide knowledge support for railway fire risk prevention and control, and facilitate the “proactive” transformation of railway safety prevention and control.KeywordsRailway fire accidentsKnowledge graphOntology modelingEntity extractionVisual presentation