{"title":"人工神经网络用于电磁逆问题的系统辨识","authors":"A. Arkadan, Y. Chen","doi":"10.1109/SECON.1994.324289","DOIUrl":null,"url":null,"abstract":"An approach which is based on the use of artificial neural networks and finite element analysis is used to solve the inverse problem of system identification. The approach is used on a test problem to identify location, material and values of unknown sources within an inaccessible region. A comparison of actual and predicted values of the unknown parameters demonstrates the validity of this approach.<<ETX>>","PeriodicalId":119615,"journal":{"name":"Proceedings of SOUTHEASTCON '94","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Artificial neural network for the inverse electromagnetic problem of system identification\",\"authors\":\"A. Arkadan, Y. Chen\",\"doi\":\"10.1109/SECON.1994.324289\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach which is based on the use of artificial neural networks and finite element analysis is used to solve the inverse problem of system identification. The approach is used on a test problem to identify location, material and values of unknown sources within an inaccessible region. A comparison of actual and predicted values of the unknown parameters demonstrates the validity of this approach.<<ETX>>\",\"PeriodicalId\":119615,\"journal\":{\"name\":\"Proceedings of SOUTHEASTCON '94\",\"volume\":\"140 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of SOUTHEASTCON '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.1994.324289\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of SOUTHEASTCON '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.1994.324289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial neural network for the inverse electromagnetic problem of system identification
An approach which is based on the use of artificial neural networks and finite element analysis is used to solve the inverse problem of system identification. The approach is used on a test problem to identify location, material and values of unknown sources within an inaccessible region. A comparison of actual and predicted values of the unknown parameters demonstrates the validity of this approach.<>