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metadata.artigo.dc.title: | Determinação de constituintes químicos em madeira de eucalipto por PI-CG/EM e calibração multivariada: comparação entre redes neurais artificiais e máquinas de vetor suporte |
metadata.artigo.dc.title.alternative: | Determination of chemical constituents in eucalyptus wood by py-gc/ms and multivariate calibration: comparison between artificial neural network and support vector machines |
metadata.artigo.dc.creator: | Nunes, Cleiton Antônio Lima, Claudio Ferreira Barbosa, Luiz Cláudio de Almeida Colodette, Jorge Luiz Fidêncio, Paulo Henrique |
metadata.artigo.dc.subject: | Analytical pyrolysis Artificial neural network Least square-support vector machine |
metadata.artigo.dc.publisher: | Sociedade Brasileira de Química |
metadata.artigo.dc.date.issued: | 27-Aug-2010 |
metadata.artigo.dc.identifier.citation: | NUNES, C. A. et al. Determinação de constituintes químicos em madeira de eucalipto por PI-CG/EM e calibração multivariada: comparação entre redes neurais artificiais e máquinas de vetor suporte. Química Nova, São Paulo, v. 34, n. 2, p. 279-283, jan./fev. 2011. |
metadata.artigo.dc.description.abstract: | Multivariate models were developed using Artificial Neural Network (ANN) and Least Square - Support Vector Machines (LS-SVM) for estimating lignin siringyl/guaiacyl ratio and the contents of cellulose, hemicelluloses and lignin in eucalyptus wood by pyrolysis associated to gaseous chromatography and mass spectrometry (Py-GC/MS). The results obtained by two calibration methods were in agreement with those of reference methods. However a comparison indicated that the LS-SVM model presented better predictive capacity for the cellulose and lignin contents, while the ANN model presented was more adequate for estimating the hemicelluloses content and lignin siringyl/guaiacyl ratio. |
metadata.artigo.dc.identifier.uri: | http://repositorio.ufla.br/jspui/handle/1/4833 |
metadata.artigo.dc.language: | pt_BR |
Appears in Collections: | DCA - Artigos publicados em periódicos |
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