DocumentCode :
2217371
Title :
Comparison of evolved epidemic networks with diffusion characters
Author :
Ashlock, Daniel ; Shiller, Elisabeth ; Lee, Colin
Author_Institution :
Math. & Stat., Univ. of Guelph, Guelph, ON, Canada
fYear :
2011
fDate :
5-8 June 2011
Firstpage :
781
Lastpage :
788
Abstract :
Epidemic models often incorporate contact net works along which the disease can be passed. This study uses a recentering-restarting evolutionary algorithm to locate likely epidemic networks for six different epidemic profiles containing early peaks, late peaks, and multiple peaks in the number of infected individuals. This study demonstrates that the algorithm can fit a broad variety of epidemic profiles. The difficulty of finding a network likely to produce a given epidemic profile varies between profiles, but all six profiles are fitted well in at least some of the evolutionary runs. A pseudometric on pairs of networks based on diffusion characters is used to assess the networks distribution in the space of networks. Both the scatter of networks evolved to match a single epidemic profile and the between-profile distances are evaluated. The diffusion character based pseudometric separates the networks for some pairs of profiles neatly while others apparently overlap to some degree.
Keywords :
diseases; evolutionary computation; diffusion characters; disease; epidemic profiles; evolved epidemic networks; infected individual; recentering-restarting evolutionary algorithm; Arrays; Data visualization; Diseases; Entropy; Evolutionary computation; Mathematics; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
ISSN :
Pending
Print_ISBN :
978-1-4244-7834-7
Type :
conf
DOI :
10.1109/CEC.2011.5949698
Filename :
5949698
Link To Document :
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