{"title":"高斯过程回归在光纤光栅温度估计中的性能分析","authors":"Sebastián San Martín, M. Soto","doi":"10.1364/ofs.2022.th4.49","DOIUrl":null,"url":null,"abstract":"The performance of Gaussian process regression for temperature estimation using fiber Bragg grating sensors is investigated. Using experiment- and simulation-based training, the estimated temperature uncertainty (standard deviation) and offset are analyzed versus different measurement parameters.","PeriodicalId":265406,"journal":{"name":"27th International Conference on Optical Fiber Sensors","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Performance Analysis of Gaussian Process Regression in the Temperature Estimation of Fiber Bragg Grating Sensors\",\"authors\":\"Sebastián San Martín, M. Soto\",\"doi\":\"10.1364/ofs.2022.th4.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performance of Gaussian process regression for temperature estimation using fiber Bragg grating sensors is investigated. Using experiment- and simulation-based training, the estimated temperature uncertainty (standard deviation) and offset are analyzed versus different measurement parameters.\",\"PeriodicalId\":265406,\"journal\":{\"name\":\"27th International Conference on Optical Fiber Sensors\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"27th International Conference on Optical Fiber Sensors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/ofs.2022.th4.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th International Conference on Optical Fiber Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/ofs.2022.th4.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Analysis of Gaussian Process Regression in the Temperature Estimation of Fiber Bragg Grating Sensors
The performance of Gaussian process regression for temperature estimation using fiber Bragg grating sensors is investigated. Using experiment- and simulation-based training, the estimated temperature uncertainty (standard deviation) and offset are analyzed versus different measurement parameters.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
