Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/61429
Type: Artigo de periódico
Title: Determination of some rare earth elements by EDXRF and artificial neural networks
Author: Schimidt, F
Cornejo-Ponce, L
Bueno, MIMS
Poppi, RJ
Abstract: This paper describes the simultaneous determination of Pr, Nd and Sm by EDXRF spectrometry using mixtures of oxides of these metals in a silica matrix. The data were treated by distinct neural network algorithms: back-propagation (BP), Levenberg-Marquardt (LM) and two variations of back-propagation (called BP-SC, single component, and BP-MC, multiple component), using results from the PLS model (partial least square regression) for comparison. The best applied model was the BP-SC neural network, which produced relative standard errors of prediction of 17.5% for Pr, 12.5% for Nd and 12.6% for Sm. Copyright (C) 2003 John Wiley Sons, Ltd.
Country: Inglaterra
Editor: John Wiley & Sons Ltd
Rights: fechado
Identifier DOI: 10.1002/xrs.662
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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