Evolutionary analysis of important public health event-based multi-agent simulation model. (1st January 2014)

• Record Type: Journal Article
• Authors: Liu, Dehai; Chen, Jingfeng; Chai, Ruirui; Wang, Weiguo
• Is Part Of: International journal of innovative computing and applications. Volume 6:Number 1(2014)
• Page Start: 33
• Page End: 43
• Publication Date: 2014-01-01
• Subjects: emergency management -- multi-agent simulation -- public health event -- evolutionary game; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

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.