{"title":"用进化算法拟合传染病行为的接触网络","authors":"D. Ashlock, E. Shiller","doi":"10.1109/CIBCB.2011.5948466","DOIUrl":null,"url":null,"abstract":"Epidemic models often incorporate contact networks along which the disease can be passed. This study incorporates a restarting-recentering evolutionary algorithm, previously developed to locate extremal epidemic networks, together with a new representation, the toggle-delete representation, for evolvable networks. The goal is to locate networks that were likely to have produced a given epidemic behavior. This goal subsumes a new fitness function for driving selection in network evolution. Earlier representations used networks with a fixed sequence of contact numbers. The new representation can add and remove edges from the network, permitting a search that varies contact numbers within the network. A parameter setting study is performed on an epidemic profile obtained from an random network and then tested on a bimodal profile invented by the researchers. The algorithm succeeds in producing networks that cause epidemics run on them to mimic the specified epidemic profiles.","PeriodicalId":395505,"journal":{"name":"2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Fitting contact networks to epidemic behavior with an evolutionary algorithm\",\"authors\":\"D. Ashlock, E. Shiller\",\"doi\":\"10.1109/CIBCB.2011.5948466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Epidemic models often incorporate contact networks along which the disease can be passed. This study incorporates a restarting-recentering evolutionary algorithm, previously developed to locate extremal epidemic networks, together with a new representation, the toggle-delete representation, for evolvable networks. The goal is to locate networks that were likely to have produced a given epidemic behavior. This goal subsumes a new fitness function for driving selection in network evolution. Earlier representations used networks with a fixed sequence of contact numbers. The new representation can add and remove edges from the network, permitting a search that varies contact numbers within the network. A parameter setting study is performed on an epidemic profile obtained from an random network and then tested on a bimodal profile invented by the researchers. The algorithm succeeds in producing networks that cause epidemics run on them to mimic the specified epidemic profiles.\",\"PeriodicalId\":395505,\"journal\":{\"name\":\"2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIBCB.2011.5948466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIBCB.2011.5948466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fitting contact networks to epidemic behavior with an evolutionary algorithm
Epidemic models often incorporate contact networks along which the disease can be passed. This study incorporates a restarting-recentering evolutionary algorithm, previously developed to locate extremal epidemic networks, together with a new representation, the toggle-delete representation, for evolvable networks. The goal is to locate networks that were likely to have produced a given epidemic behavior. This goal subsumes a new fitness function for driving selection in network evolution. Earlier representations used networks with a fixed sequence of contact numbers. The new representation can add and remove edges from the network, permitting a search that varies contact numbers within the network. A parameter setting study is performed on an epidemic profile obtained from an random network and then tested on a bimodal profile invented by the researchers. The algorithm succeeds in producing networks that cause epidemics run on them to mimic the specified epidemic profiles.