A Simulation Study for Emergency/Disaster Management by Applying Complex Networks Theory

 

Li Jin¹, Wang Jiong²*, Dai Yang³, Wu Huaping⁴ and Dong Wei⁵

 

^{1, 4} Earthquake Administration of Guangdong Province, Key Laboratory of Earthquake Monitoring and Disaster Mitigation Technology, CEA; Key Laboratory of Earthquake early Warning and Safety Diagnosis of Major Project, Guangdong, China.

² School of Electrical Engineering, North China University of Water Resources and Electric Power, ZhengZhou 450011, China.

³ School of Economics and Management, Southwest Jiaotong University, ChengDu, China.

⁵ Deparment of information Systems, USTC-CityU Jiont Advanced Research Centre, China. * kfwjd@ncwu.edu.cn

 

ABSTRACT

Earthquakes, hurricanes, flooding and terrorist attacks pose a severe threat to our society. What's more, when such a disaster happens, it can spread in a wide range with ubiquitous presence of a large-scale networked system. Therefore, the emergency/disaster management faces new challenges that the decision-makers have extra difficulties in perceiving the disaster dynamic spreading processes under this networked environment. This study tries to use the complex networks theory to tackle this complexity and the result shows the theory is a promising approach to support disaster/emergency management by focusing on simulation experiments of small world networks and scale free networks. The theory can be used to capture and describe the evolution mechanism, evolution discipline and overall behavior of a networked system. In particular, the complex networks theory is very strong at analyzing the complexity and dynamical changes of a networked system, which can improve the situation awareness after a disaster has occurred and help perceive its dynamic process, which is very important for high-quality decision making. In addition, this study also shows the use of the complex networks theory can build a visualized process to track the dynamic spreading of a disaster in a networked system.

Keywords: Disaster Management, Emergency Management, Complex Networks Theory, Small World Network, Scale Free Network.

 

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