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