{"title":"一种新的自适应免疫遗传算法","authors":"Zheng Chang, G. Zhu","doi":"10.1109/KAM.2009.21","DOIUrl":null,"url":null,"abstract":"The theories of machine-learning are applied to the immune genetic algorithm. Chromosomes' immunity is enhanced and the average fitness of chromosomes is improved by using adaptive vaccine, so as to avoid the loss of the best solution, shrink the searching space and speed up the evolution, then the best solution can be get earlier. At the same time, the results are compared with each other through the optimization calculation of the modified immune genetic algorithm and the traditional genetic algorithm in solving classic 3x3 JSP problem.","PeriodicalId":192986,"journal":{"name":"2009 Second International Symposium on Knowledge Acquisition and Modeling","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Adaptive Immune Genetic Algorighm\",\"authors\":\"Zheng Chang, G. Zhu\",\"doi\":\"10.1109/KAM.2009.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The theories of machine-learning are applied to the immune genetic algorithm. Chromosomes' immunity is enhanced and the average fitness of chromosomes is improved by using adaptive vaccine, so as to avoid the loss of the best solution, shrink the searching space and speed up the evolution, then the best solution can be get earlier. At the same time, the results are compared with each other through the optimization calculation of the modified immune genetic algorithm and the traditional genetic algorithm in solving classic 3x3 JSP problem.\",\"PeriodicalId\":192986,\"journal\":{\"name\":\"2009 Second International Symposium on Knowledge Acquisition and Modeling\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Symposium on Knowledge Acquisition and Modeling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KAM.2009.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Symposium on Knowledge Acquisition and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KAM.2009.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The theories of machine-learning are applied to the immune genetic algorithm. Chromosomes' immunity is enhanced and the average fitness of chromosomes is improved by using adaptive vaccine, so as to avoid the loss of the best solution, shrink the searching space and speed up the evolution, then the best solution can be get earlier. At the same time, the results are compared with each other through the optimization calculation of the modified immune genetic algorithm and the traditional genetic algorithm in solving classic 3x3 JSP problem.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
