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Chinese Journal of Management Science ›› 2021, Vol. 29 ›› Issue (10): 165-177.doi: 10.16381/j.cnki.issn1003-207x.2017.1561

• Articles • Previous Articles    

Modeling Method of Concurrent Emergency Chain Based on Bayesian Network

CHEN Xuelong, JIANG Kun   

  1. School of Economics and Management, Dalian University of Technology, Dalian 116024, China
  • Received:2017-11-17 Revised:2018-04-09 Online:2021-10-20 Published:2021-10-21

Abstract: In realistic circumstances, because of the similarities between the hazard factors and their affected objects in different emergencies, the occurrence of initial emergencies is likely to trigger the concurrence and coupling of multiple secondary emergencies, which makes the evolution of emergencies more uncertain and causes more serious losses. However, the existing emergency chain evolution analyses mostly used serial emergency chains, which is less applicable to concurrent emergencies. In view of the above problems, this paper presents a modeling method of concurrent emergency chain based on Bayesian Network to model the parallel evolution of concurrent emergencies. Firstly, emergency is described as a complex system composed of input, state, output attributes and the mutual influence relationships between them. And the causality and coupling relationships between emergencies are analyzed and defined on attribute level. Secondly, Bayesian network is applied to represent a single emergency formally. Based on the defined causality and coupling relationships between emergencies, the identification method of the causality and coupling relationships between single emergency Bayesian networks, the association method of concurrent emergency Bayesian networks, and the concrete construction method of the Bayesian network on concurrent emergency chain are put forward. Thirdly, the reasoning algorithm and its complexity and feasibility of the constructed concurrent emergencies Bayesian network are discussed. Through the Bayesian network reasoning process, the evolution analysis of concurrency emergencies can be realized in case of the prior probabilities between network nodes are obtained based on historical data analysis. Finally, to demonstrate the feasibility and validity of the proposed methods, the historical data of rainstorm disasters and the subsequent secondary disasters, such as mudslides, landslides, and floods and so on, in Sichuan Province from 2008 to 2015 is collected. Then the K2 network learning method is used to study the historical data to generate the Bayesian network of each disaster. Based on the identification of the interrelationships between the single Bayesian networks corresponding to each disaster, the integrated Bayesian network is constructed by correlating the interrelated single Bayesian networks. Taking the rainstorm disaster happened in August 16, 2015 in Yibin City as an example to instantiate the initial evidence information of the constructed integrated Bayesian network, the joint tree reasoning method is applied to predict the possible losses caused by the rainstorm and its derivative disasters. The analyses of the prediction result and the comparison with related serial emergency chains verify the scientificalness and effectiveness of the proposed methods while being used in evolution analysis of concurrent emergencies.

Key words: emergency chain, concurrent emergencies, coupling effect, bayesian network

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