{"title":"核偏最小二乘法同时分光光度法测定锰、锌和钴。","authors":"L Gao, S Ren","doi":"10.1155/S1463924698000224","DOIUrl":null,"url":null,"abstract":"<p><p>Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deducing the number of factors. Data reductions were performed using principle component analysis. The KPLS method was applied for the rapid determination from a data matrix with many wavelengths and fewer numbers of samples. The relative standard errors of prediction (RSEP) for all components with KPLS and PLS methods were the same (0.0247). Experimental results showed both methods to be successful even where there was severe overlap of spectra.</p>","PeriodicalId":22600,"journal":{"name":"The Journal of Automatic Chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1998-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/S1463924698000224","citationCount":"14","resultStr":"{\"title\":\"Simultaneous spectrophotometric determination of manganese, zinc and cobalt by kernel partial least-squares method.\",\"authors\":\"L Gao, S Ren\",\"doi\":\"10.1155/S1463924698000224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deducing the number of factors. Data reductions were performed using principle component analysis. The KPLS method was applied for the rapid determination from a data matrix with many wavelengths and fewer numbers of samples. The relative standard errors of prediction (RSEP) for all components with KPLS and PLS methods were the same (0.0247). Experimental results showed both methods to be successful even where there was severe overlap of spectra.</p>\",\"PeriodicalId\":22600,\"journal\":{\"name\":\"The Journal of Automatic Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/S1463924698000224\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Automatic Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/S1463924698000224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Automatic Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/S1463924698000224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simultaneous spectrophotometric determination of manganese, zinc and cobalt by kernel partial least-squares method.
Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deducing the number of factors. Data reductions were performed using principle component analysis. The KPLS method was applied for the rapid determination from a data matrix with many wavelengths and fewer numbers of samples. The relative standard errors of prediction (RSEP) for all components with KPLS and PLS methods were the same (0.0247). Experimental results showed both methods to be successful even where there was severe overlap of spectra.