{"title":"基于遗传规划的模型自动选择算法","authors":"Yanghe Feng, Chaofan Dai, Jianmai Shi, Liang Mu","doi":"10.1109/IEEC.2010.5533243","DOIUrl":null,"url":null,"abstract":"The usability of model-aided decision relies on intellectualized level of model selection. An algorithm of Model selection based sample data is proposed in the paper. The meta-models are classified by characters of the sample data, and the assembled models are built as tree format. The genetic operations are performed under several restrictions to provide the model selection scheme. Its process hardly depends on user's knowledge on domain.","PeriodicalId":307678,"journal":{"name":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Automatic Model Selection Algorithm Based Genetic Programming\",\"authors\":\"Yanghe Feng, Chaofan Dai, Jianmai Shi, Liang Mu\",\"doi\":\"10.1109/IEEC.2010.5533243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The usability of model-aided decision relies on intellectualized level of model selection. An algorithm of Model selection based sample data is proposed in the paper. The meta-models are classified by characters of the sample data, and the assembled models are built as tree format. The genetic operations are performed under several restrictions to provide the model selection scheme. Its process hardly depends on user's knowledge on domain.\",\"PeriodicalId\":307678,\"journal\":{\"name\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEC.2010.5533243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEC.2010.5533243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Automatic Model Selection Algorithm Based Genetic Programming
The usability of model-aided decision relies on intellectualized level of model selection. An algorithm of Model selection based sample data is proposed in the paper. The meta-models are classified by characters of the sample data, and the assembled models are built as tree format. The genetic operations are performed under several restrictions to provide the model selection scheme. Its process hardly depends on user's knowledge on domain.
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