Artículos de revistas
Determination of diesel quality parameters using support vector regression and near infrared spectroscopy for an in-line blending optimizer system
Registro en:
Fuel. Elsevier Sci Ltd, v. 97, n. 710, n. 717, 2012.
0016-2361
WOS:000303979400080
10.1016/j.fuel.2012.03.016
Autor
Alves, JCL
Henriques, CB
Poppi, RJ
Institución
Resumen
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) This work demonstrates the application of support vector regression (SVR) applied to near infrared spectroscopy (NIR) data to solve regression problems associated to determination of quality parameters of diesel oil for an in-line blending optimizer system in a petroleum refinery. The determination of flash point and cetane number was performed using SVR and the results were compared with those obtained by using the PLS algorithm. A parametric optimization using a genetic algorithm was carried out for choice of the parameters in the SVR regression models. The best models using SVR presented a RBF kernel and spectra preprocessed with baseline correction and mean centered data. The obtained values of RMSEP with the SVR models are 1.98 degrees C and 0.453 for flash point and cetane number, respectively. The SVR provided significantly better results when compared with PLS and in agreement with the specification of the ASTM reference method for both quality parameter determinations. (C) 2012 Elsevier Ltd. All rights reserved. 97 710 717 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)