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

• Autor(a) principal: Nunes,Cleiton Antônio
• Data de Publicação: 2011
• Outros Autores: Lima,Claudio Ferreira, Barbosa,Luiz Cláudio de Almeida, Colodette,Jorge Luiz, Fidêncio,Paulo Henrique
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Química Nova (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422011000200020
• topic: analytical pyrolysis; artificial neural network; least square-support vector machine

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.