{"title":"基于人工神经网络响应面技术的多学科设计优化研究","authors":"Hanyun Wen, Jie Hu","doi":"10.1109/WGEC.2009.28","DOIUrl":null,"url":null,"abstract":"In the paper, we constructed the response surface mold through the neural network, elaborated the concept and mathematics description of the response surface. Through a real example, we solved the coupling relationship during multidisciplinary as well as the synthesis coordination of many disciplines with multidisciplinary design based on the response surface. We completed the data exchanging and coordinating during each sub-discipline through the response surface of neural network and approached the optimal solution. The research indicates that the response face mold constructed with neural network can reduce the analysis time and enhance the precision to a great extent and help us seek for better design finally.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"217 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Multidisciplinary Design Optimization Based Response Surface Technology of Artificial Neural Network\",\"authors\":\"Hanyun Wen, Jie Hu\",\"doi\":\"10.1109/WGEC.2009.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper, we constructed the response surface mold through the neural network, elaborated the concept and mathematics description of the response surface. Through a real example, we solved the coupling relationship during multidisciplinary as well as the synthesis coordination of many disciplines with multidisciplinary design based on the response surface. We completed the data exchanging and coordinating during each sub-discipline through the response surface of neural network and approached the optimal solution. The research indicates that the response face mold constructed with neural network can reduce the analysis time and enhance the precision to a great extent and help us seek for better design finally.\",\"PeriodicalId\":277950,\"journal\":{\"name\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"volume\":\"217 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Third International Conference on Genetic and Evolutionary Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WGEC.2009.28\",\"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 Third International Conference on Genetic and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WGEC.2009.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Multidisciplinary Design Optimization Based Response Surface Technology of Artificial Neural Network
In the paper, we constructed the response surface mold through the neural network, elaborated the concept and mathematics description of the response surface. Through a real example, we solved the coupling relationship during multidisciplinary as well as the synthesis coordination of many disciplines with multidisciplinary design based on the response surface. We completed the data exchanging and coordinating during each sub-discipline through the response surface of neural network and approached the optimal solution. The research indicates that the response face mold constructed with neural network can reduce the analysis time and enhance the precision to a great extent and help us seek for better design finally.