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dc.contributor.authorPeng, Chengbin
dc.contributor.authorWang, Shengbin
dc.contributor.authorShi, Meixia
dc.contributor.authorJin, Xiaogang
dc.date.accessioned2015-08-04T06:24:31Z
dc.date.available2015-08-04T06:24:31Z
dc.date.issued2011
dc.identifier.isbn9783642256578
dc.identifier.issn18675662
dc.identifier.doi10.1007/978-3-642-25658-5_44
dc.identifier.urihttp://hdl.handle.net/10754/564349
dc.description.abstractIn the current century, the highly developed transportation system can not only boost the economy, but also greatly accelerate the spreading of epidemics. While some epidemic diseases may infect quite a number of people ahead of our awareness, the health care resources such as vaccines and the medical staff are usually locally or even globally insufficient. In this research, with the network of major aviation routes as an example, we present a method to determine the optimal locations to allocate the medical service in order to minimize the impact of the infectious disease with limited resources. Specifically, we demonstrate that when the medical resources are insufficient, we should concentrate our efforts on the travelers with the objective of effectively controlling the spreading rate of the epidemic diseases. © 2011 Springer-Verlag Berlin Heidelberg.
dc.publisherSpringer Nature
dc.subjectAviation Networks
dc.subjectEpidemic Control
dc.subjectSIS Model
dc.titleUrgent epidemic control mechanism for aviation networks
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.identifier.journalPractical Applications of Intelligent Systems
dc.conference.date2011-12-01
dc.conference.nameProceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering
dc.conference.locationShanghai, China
dc.contributor.institutionRutgers Business School, Rutgers University, Newark, NJ 07102, United States
dc.contributor.institutionCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310027, China
dc.contributor.institutionInstitute of Artificial Intelligence, College of Computer Science, Zhejiang University, Hangzhou 310027, China
kaust.personPeng, Chengbin


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