Construction and application of knowledge graph for urban agglomeration emergency rescue collaboration in earthquake disasters

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
安全科学与韧性(英文) Pub Date : 2026-03-01 Epub Date: 2025-09-04 DOI:10.1016/j.jnlssr.2025.100253
Lin Zhang , Qichen Wang , Yanjun Guo , Xiangliang Tian , Lin Qi
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引用次数: 0

Abstract

This study proposes an emergency rescue collaboration knowledge graph construction method for urban agglomeration in earthquake disasters. Based on the collection of 22 earthquake disaster emergency plans published on the official websites of multiple cities in the Chengdu-Chongqing urban agglomeration in China, earthquake disaster emergency rescue data from the Red Cross Society of Sichuan Province and Chongqing City, and historical rescue information from the China Blue Sky rescue team, this study defines and extracts six types of entities including rescue entities, policy documents, rescue actions, rescue information, rescue supplies, and emergency response levels. A knowledge graph pattern layer is established using a hybrid approach of top-down and bottom-up, including concept layer, relationship layer, rule layer, and instance layer. This study extracts earthquake disaster emergency rescue collaboration knowledge information from collected data sources, and YEDDA software is used for knowledge fusion, thus constructing a knowledge graph data layer. The data is stored in the Neo4j graph database as triplets (entity-relation-entity). Visual representation and retrieval are used to achieve the query, association, and inference of emergency rescue collaboration information for urban agglomeration in earthquake disasters. The 2022 Luding earthquake disaster in Ganzi Tibetan Autonomous Prefecture, China is selected as a typical case, and verified the effectiveness and reliability by inputting the case into the emergency rescue collaboration knowledge graph which was constructed in this study. The results indicate that the constructed knowledge graph provides intelligent decision support for earthquake disaster emergency rescue collaboration in urban agglomeration, effectively improves the performance of earthquake disaster emergency rescue, and provides new ideas and methods for earthquake disaster rescue and reduction.
城市群地震灾害应急救援协同知识图谱的构建与应用
本文提出了一种城市群地震灾害应急救援协同知识图谱构建方法。本研究在收集成渝城市群多个城市官方网站发布的22份地震灾害应急预案、四川省红十字会和重庆市红十字会的地震灾害应急救援数据、中国蓝天救援队的历史救援信息的基础上,定义并提取了救援主体、政策文件、救援行动、救援信息、救援物资和应急响应水平。采用自顶向下和自底向上混合的方法建立知识图谱模式层,包括概念层、关系层、规则层和实例层。本研究从采集到的数据源中提取地震灾害应急救援协同知识信息,利用YEDDA软件进行知识融合,构建知识图谱数据层。数据以三元组(实体-关系-实体)的形式存储在Neo4j图形数据库中。采用可视化表示和检索技术,实现了地震灾害下城市群应急救援协同信息的查询、关联和推理。结果表明,构建的知识图谱为城市群地震灾害应急救援协同提供了智能决策支持,有效提高了地震灾害应急救援性能,为地震灾害救援减灾提供了新的思路和方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
安全科学与韧性(英文)
安全科学与韧性(英文) Management Science and Operations Research, Safety, Risk, Reliability and Quality, Safety Research
CiteScore
8.70
自引率
0.00%
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0
审稿时长
72 days
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