Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/1995
Title: Determination of octane number of gasoline using near infrared spectroscopy and genetic multivariate calibration methods
Authors: Özdemir, Durmuş
Özdemir, Durmuş
Keywords: Antiknock rating
Calibration
Diffusion
Error analysis
Genetic algorithms
Infrared spectroscopy
Least squares approximations
Issue Date: Sep-2005
Publisher: Taylor and Francis Ltd.
Source: Özdemir, D. (2005). Determination of octane number of gasoline using near infrared spectroscopy and genetic multivariate calibration methods. Petroleum Science and Technology, 23(9-10). 1139-1152. doi:10.1081/LFT-200035547
Abstract: The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy and three different genetic algorithm-based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are genetic regression (GR), genetic classical least squares (GCLS), and genetic inverse least squares (GILS). The sample data set was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) with the permission of Professor. J. H. Kalivas. This data set contains the NIR spectra of 60 gasoline samples collected using diffuse reflectance as log (I / R) with known octane numbers and covers the range from 900 to 1700 nm in 2 nm intervals. Of these 60 spectra, 20 were used as the calibration set, 20 were used as the prediction set, and 20 were reserved for the validation purposes. Several calibration models were built with the three genetic algorithm-based methods, and the results were compared with the partial least squares (PLS) prediction errors reported in the literature. Overall, the standard error of calibration (SEC), standard error of prediction (SEP), and standard error of validation (SEV) values were in the range of 0.15-0.32 (in the units of motor octane number) for the GR and GILS, which are comparable with the literature. However, GCLS produced relatively large results (0.36 for SEC, 0.39 for SEP and 0.52 for SEV) when compared with the other two methods.
URI: http://doi.org/10.1081/LFT-200035547
http://hdl.handle.net/11147/1995
ISSN: 1091-6466
1532-2459
1091-6466
Appears in Collections:Chemistry / Kimya
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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