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Using an Evolutionary Algorithm for the Optimization of Epidemic Surveillance and Control in Networks

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dc.contributor.advisor Dr. Raphael Duboz (Chairperson)
dc.contributor.author Palotaitakerng, Chaipichet
dc.contributor.other Prof. Phan Minh Dung (Member) Prof. Sumanta Guha (Member)
dc.date.accessioned 2015-02-03T01:49:01Z
dc.date.available 2015-02-03T01:49:01Z
dc.date.issued 2013-05
dc.identifier.other AIT Thesis no.IM-13-03 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/720
dc.description.abstract In this research study, we applied an evolutionary algorithm (EA) to study the optimization of epidemic surveillance and control in networks. We use a simulation of infectious disease stochastically spread in network as a tool. Disease spread in the simulation is based on the susceptible-infected-recovered (SIR) epidemic model. The EA evaluates the fitness of each solution by the results of the simulation. The EA is applied to obtain the optimum outcomes, the sets of the optimum value for the variables of epidemic surveillance and control. The optimum outcomes exhibit low infected population and low cost of the surveillance and control. The results which are obtained by using EA have been studied to conclude the effects of network topology and EA fitness function to the results. en_US
dc.description.sponsorship Royal Thai Government - AIT Fellowship en_US
dc.publisher AIT en_US
dc.subject evolutionary algorithm, SIR epidemic model, disease spread in networks, surveillance and control, simulation, network topology en_US
dc.title Using an Evolutionary Algorithm for the Optimization of Epidemic Surveillance and Control in Networks en_US
dc.type Thesis en_US


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