基于知识图谱的暴雨灾害链挖掘与预测研究  

Mining and Forecasting of Rainstorm Disaster Chain Based on Knowledge Graph

作　　者：黄晶[1,2] 吴星妍[1] 王慧敏 戴强[3] HUANG Jing;WU Xingyan;WANG Huimin;DAI Qiang(Business School,Hohai University,Nanjing 211100,China;The National Key Laboratory of Water Disaster Prevention,Nanjing 210024,China;School of Geography,Nanjing Normal University,Nanjing 210023,China)

机构地区：[1]河海大学商学院,江苏南京211100 [2]河海大学水灾害防御全国重点实验室,江苏南京210024 [3]南京师范大学地理科学学院,江苏南京210023

出　　处：《工程管理科技前沿》2024年第4期46-53,共8页Frontiers of Science and Technology of Engineering Management

基　　金：国家自然科学基金资助项目(42171081,42371092,72174054);国家自然科学基金重大研究计划重点资助项目(91846203)。

摘　　要：暴雨灾害不仅会引发崩滑流、内涝等次生灾害,更会造成交通中断、供电中断、市政设施损毁等一系列衍生后果,这种现象被称为暴雨灾害链。为了把握暴雨灾害链演化发展的客观规律,有效防范暴雨灾害链的风险,本文提出了一种基于知识图谱的暴雨灾害链挖掘与预测方法。首先,将承灾体影响纳入暴雨灾害链本体模型,构建了暴雨灾害链知识图谱;其次,提出了基于链路耦合的暴雨灾害链挖掘方法,构建了基于贝叶斯网络的暴雨灾害链预测模型;再次,以珠三角地区为例,挖掘暴雨灾害链,并预测某次暴雨事件的灾害链。结果表明:①构建的暴雨灾害链知识图谱能够全面展示出暴雨次生灾害链及其衍生的承灾体后果;②基于知识图谱链路耦合的暴雨灾害链挖掘方法完整地挖掘出了暴雨灾害链,主要类型包括自然灾害类、城市生命线影响类、人员伤亡类、设备和建筑事故类、生产生活潜在影响类;③提出的基于贝叶斯网络的暴雨灾害链预测模型,在暴雨灾害发生初期就能准确预测出暴雨灾害链的发生概率。In recent years,under the influence of climate change and urbanization,extreme rainstorm events in urbanized areas have been increasing in China.Rainstorm disasters not only trigger secondary disasters such as landslides and urban flooding,but also result in a series of derivative consequences such as transportation interruptions,power outages,and damage to municipal facilities.This phenomenon,where rainstorms serve as direct or indirect factors inducing a series of secondary and derivative disasters to occur consecutively,is called a rainstorm disaster chain.It often exhibits cumulative and unpredictable characteristics,making its evolution and development difficult to predict and control.With the development of big data technology,it is possible to transform massive data into knowledge,providing a new approach for risk prediction of rainstorm disaster chain.This paper aims to explore the evolution process of rainstorm disaster chain and predict the secondary disasters and derivative consequences,and thereby prevent the risk of rainstorm disaster chain effectively.In this paper,a knowledge graph for rainstorm disaster chain is constructed,incorporating the impact on vulnerable entities into the conceptual layer of rainstorm disaster chain ontology model.Then,a rainstorm disaster chain mining method is proposed based on link coupling of knowledge graph.By mapping the knowledge graph to Bayesian network structure,rainstorm disaster chain prediction model based on Bayesian networks is constructed.Finally,focusing on the Pearl River Delta region as the study area,various types of rainstorm disaster chains are explored,and the secondary disasters and derivative consequences are predicted by taking the“8.29 Shenzhen Rainstorm”event as an example.The research results indicate that:(1)The knowledge graph constructed based on rainstorm disaster chain ontology model can not only depict the secondary disaster but also illustrate the derivative consequences such as infrastructure damage,casualties,and potential impacts

关 键 词：暴雨灾害 灾害链挖掘 概率预测 知识图谱 贝叶斯网络 

分 类 号：C93[经济管理—管理学]