{"title":"基于多目标遗传算法的超磁致伸缩智能元件优化","authors":"X. Sui, Zhang-Rong Zhao, Xu-Ming Wang, Xia-Jun Meng","doi":"10.1109/ICNC.2010.5583153","DOIUrl":null,"url":null,"abstract":"In order to machine the non-cylinder piston pinhole, a new method is proposed by applying the Giant magnetostrictive materials (GMM) component. An optimization design model combining the smart component genetic algorithm with the finite element method for GMM smart component is established. Nondominated sorting genetic algorithm (NSGA) is used to optimize the model. The optimum results show that the NSGA combining with finite element method is a good way to carry out the optimization design of GMM smart component.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"75 1","pages":"466-470"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization for Giant magnetostrictive smart component based on multi-objective genetic algorithm\",\"authors\":\"X. Sui, Zhang-Rong Zhao, Xu-Ming Wang, Xia-Jun Meng\",\"doi\":\"10.1109/ICNC.2010.5583153\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to machine the non-cylinder piston pinhole, a new method is proposed by applying the Giant magnetostrictive materials (GMM) component. An optimization design model combining the smart component genetic algorithm with the finite element method for GMM smart component is established. Nondominated sorting genetic algorithm (NSGA) is used to optimize the model. The optimum results show that the NSGA combining with finite element method is a good way to carry out the optimization design of GMM smart component.\",\"PeriodicalId\":87274,\"journal\":{\"name\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"volume\":\"75 1\",\"pages\":\"466-470\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2010.5583153\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2010.5583153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization for Giant magnetostrictive smart component based on multi-objective genetic algorithm
In order to machine the non-cylinder piston pinhole, a new method is proposed by applying the Giant magnetostrictive materials (GMM) component. An optimization design model combining the smart component genetic algorithm with the finite element method for GMM smart component is established. Nondominated sorting genetic algorithm (NSGA) is used to optimize the model. The optimum results show that the NSGA combining with finite element method is a good way to carry out the optimization design of GMM smart component.
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