Simultaneous determination of lead and sulfur by energy-dispersive x-ray spectrometry. Comparison between artificial neural networks and other multivariate calibration methods

dc.creatorFacchin, I
dc.creatorMello, C
dc.creatorBueno, MIMS
dc.creatorPoppi, RJ
dc.date1999
dc.dateMAY-JUN
dc.date2014-12-02T16:30:15Z
dc.date2015-11-26T17:39:28Z
dc.date2014-12-02T16:30:15Z
dc.date2015-11-26T17:39:28Z
dc.date.accessioned2018-03-29T00:21:03Z
dc.date.available2018-03-29T00:21:03Z
dc.identifierX-ray Spectrometry. John Wiley & Sons Ltd, v. 28, n. 3, n. 173, n. 177, 1999.
dc.identifier0049-8246
dc.identifierWOS:000081035800009
dc.identifier10.1002/(SICI)1097-4539(199905/06)28:3<173
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/74207
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/74207
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/74207
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1286460
dc.descriptionThe need for mathematical methods to model data in energy-dispersive x-ray fluorescence (EDXRF) spectrometry is common owing to the overlapping of intense spectral lines in complex samples. This overlapping generally produces a large amount of scatter in the analytical curve, preventing simultaneous direct determinations of some elements without data treatment. This work demonstrates the performance of artificial neural networks (ANN) and other methods of multivariate calibration (linear or not) for the simultaneous determination of sulfur and lead, when overlapping of the sulfur K alpha spectral line (2.308 keV) and the lead M alpha line (2.346 keV) is observed. The performance of neural networks was compared by the f-test with five other data treatment methods: PLS (partial least squares), POLYPLS (polynomial partial least squares), NNPLS (partial least square neural networks), LR (linear regression) and CI (corrected intensity). It was verified that the ANN produces better predictions than the other methods, for both sulfur and lead, allowing their simultaneous determination in solid samples with good accuracy. Copyright (C) 1999 John Wiley & Sons, Ltd.
dc.description28
dc.description3
dc.description173
dc.description177
dc.languageen
dc.publisherJohn Wiley & Sons Ltd
dc.publisherW Sussex
dc.publisherInglaterra
dc.relationX-ray Spectrometry
dc.relationX-Ray Spectrom.
dc.rightsfechado
dc.rightshttp://olabout.wiley.com/WileyCDA/Section/id-406071.html
dc.sourceWeb of Science
dc.subjectFluorescence Analysis
dc.subjectRegression
dc.subjectElements
dc.subjectSquares
dc.titleSimultaneous determination of lead and sulfur by energy-dispersive x-ray spectrometry. Comparison between artificial neural networks and other multivariate calibration methods
dc.typeArtículos de revistas


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