Comparison of different calibration methods for the determination by FT-NIR spectroscopy of the hydroxyl number in polyester resins.
Different calibration methods have been applied for the determination of the Hydroxyl Number in polyester resins, namely Partial Least Squares (PLS), Principal Component Regression (PCR), Ordinary Least Squares with selection of the variables by genetic algorithm (OLS-GEN) and back-propagation Artificial Neural Networks (BP-ANN). The predictive ability of the regression models was estimated by splitting the dataset in training and test sets by application of the Kohonen self-organising maps. The linear methods (OLS-GEN, PLS and PCR) showed comparable results while artificial neural networks provided the best results both in fitting and prediction.
Marengo
Emilio
E
Università del Piemonte Orientale "Amedeo Avogadro", Dipartimento di Scienze e Tecnologie Avanzate, Spalto Marengo 33, 15100 Alessandria, Italy. marengoe@tin.it
Soave
Cristina
C
Gennaro
Maria Carla
MC
Robotti
Elisa
E
Bobba
Marco
M
Lenti
Marcello
M
D002138:Calibration; D016014:Linear Models; D008432:Mathematical Computing; D016571:Neural Networks, Computer; D011091:Polyesters / Q000737:chemistry*; D012117:Resins, Synthetic / Q000737:chemistry*; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data
D011091:Polyesters; D012117:Resins, Synthetic