M. F. Pantoja, Jesus B. Rodriguez, A. Bretones, C. M. de Jong, S. Garcia, R. Martín, D. Vieira
{"title":"Application of neural network and principal component analysis to GPR data","authors":"M. F. Pantoja, Jesus B. Rodriguez, A. Bretones, C. M. de Jong, S. Garcia, R. Martín, D. Vieira","doi":"10.1109/IWAGPR.2011.5963854","DOIUrl":null,"url":null,"abstract":"This communication presents a prediction algorithm for the detection of features in GPR-based surveys. Based on signal processing and soft-computing techniques, the coupled use of principal-component analysis and neural networks enables a definition of an efficient method for analyzing GPR electromagnetic data. Results for detecting features of geological layers demonstrate not only the accuracy of the predictions of the method but also the simple interpretation of its output through reconstructed images of the scenarios.","PeriodicalId":130006,"journal":{"name":"2011 6th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWAGPR.2011.5963854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This communication presents a prediction algorithm for the detection of features in GPR-based surveys. Based on signal processing and soft-computing techniques, the coupled use of principal-component analysis and neural networks enables a definition of an efficient method for analyzing GPR electromagnetic data. Results for detecting features of geological layers demonstrate not only the accuracy of the predictions of the method but also the simple interpretation of its output through reconstructed images of the scenarios.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
