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Int. J. of Innovative Computing and Applications: Evolutionary analysis of important public health event-based multi-agent simulation model

tetano

Editor, Senior Moderator
Title: Evolutionary analysis of important public health event-based multi-agent simulation model


Author: Dehai Liu; Jingfeng Chen; Ruirui Chai; Weiguo Wang


Address: Center of Econometric Analysis and Forecasting, Dongbei University of Finance and Economics, Dalian, Liaoning, China ' Center of Econometric Analysis and Forecasting, Dongbei University of Finance and Economics, Dalian, Liaoning, China ' Department of Computer Science, Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian, Liaoning, China ' Center of Econometric Analysis and Forecasting, Dongbei University of Finance and Economics, Dalian, Liaoning, China


Journal: Int. J. of Innovative Computing and Applications, 2014 Vol.6, No.1, pp.33 - 43


Abstract: The evolutionary mechanism and emergency management of some important public health events are one of the great challenges of human society. The paper analyses the evolutionary mechanism of epidemic situation used evolutionary game theory, where government departments take the different degrees of prevention and control measures aimed to the behaviours of social public. According to the evolutionary function, the diffusion speed of epidemic situation depends on the initial state and strategies profile's payoffs. As an exogenous parameter, the initial state can be assumed as multiple scenarios. In the case of Chinese influenza A (H1N1) in 2009, the paper makes multi-agent simulation analysis of evolutionary mechanism of epidemic situation under the NetLogo simulation platform. The simulation results show that epidemic situation maybe have four evolutionary scenarios. The actual case from influenza A (H1N1) accords with the first scenarios, i.e., active prevention and control.


Keywords: emergency management; multi-agent simulation; public health events; evolutionary games; modelling; multi-agent systems; MAS; agent-based systems; disease epidemics; influenza A; H1N1; swine flu; disease prevention; disease control.


DOI: 10.1504/IJICA.2014.064218

http://www.inderscience.com/info/inarticle.php?artid=64218
 
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