Genetic Multivariate Calibration Methods for Near Infrared (NIR) Spectroscopic Determination of Complex Mixtures

Durmuş ÖZDEMİR and Betül ÖZTÜRK

Makale detayları

Genetic Multivariate Calibration Methods for Near Infrared (NIR) Spectroscopic Determination of Complex Mixtures

Yazarlar:

Durmuş ÖZDEMİR and Betül ÖZTÜRK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Chemistry 2004 Vol.28 Issue 4, pp.497-514

Belge Tipi:

Makale

Yayın Tarihi:

3/2004

Belge Dili:

Türkçe

Document ID (Org No.):

2000729309

Sıklık:

İki Aylık

eISSN:

1303-6130

pISSN:

1300-0527

Özet:

 

The simultaneous determination of ternary mixtures of  methylene chloride, ethyl acetate, and methanol using near infrared  (NIR) spectroscopy and 4 different genetic algorithms based  multivariate calibration methods was demonstrated.  The 4 genetic  multivariate calibration methods are genetic partial least squares  (GPLS), genetic regression (GR), genetic classical least squares  (GCLS) and genetic inverse least squares (GILS).  The sample data set  contains the NIR spectra of 63 ternary mixtures and covers the range  from 900 to 2000 nm in 2 nm intervals.  Of these 63 spectra, 42 were  used as the calibration set, and 21 were reserved for the prediction  purposes.  Several calibration models were built with the 4 genetic  algorithm based methods for each component that makes up the mixtures.   Overall, the standard error of calibration (SEC) and the standard  error of prediction (SEP) were in the range of 0.22 to 2.5 (% by  volume (v/v)) for all the 4 methods.  A comparison of genetic  algorithm selected wavelengths for each component and for each method  was also included.

 

The simultaneous determination of ternary mixtures of  methylene chloride, ethyl acetate, and methanol using near infrared  (NIR) spectroscopy and 4 different genetic algorithms based  multivariate calibration methods was demonstrated.  The 4 genetic  multivariate calibration methods are genetic partial least squares  (GPLS), genetic regression (GR), genetic classical least squares  (GCLS) and genetic inverse least squares (GILS).  The sample data set  contains the NIR spectra of 63 ternary mixtures and covers the range  from 900 to 2000 nm in 2 nm intervals.  Of these 63 spectra, 42 were  used as the calibration set, and 21 were reserved for the prediction  purposes.  Several calibration models were built with the 4 genetic  algorithm based methods for each component that makes up the mixtures.   Overall, the standard error of calibration (SEC) and the standard  error of prediction (SEP) were in the range of 0.22 to 2.5 (% by  volume (v/v)) for all the 4 methods.  A comparison of genetic  algorithm selected wavelengths for each component and for each method  was also included.

Makale detayları

Genetic Multivariate Calibration Methods for Near Infrared (NIR) Spectroscopic Determination of Complex Mixtures

Yazarlar: Durmuş ÖZDEMİR and Betül ÖZTÜRK

Yayıncı: TUBITAK

Dergi: Turkish Journal of Chemistry 2004 Vol.28 Issue 4, pp.497-514

Belge Tipi: Makale

Yayın Tarihi: 3/2004

Belge Dili: Türkçe

Document ID (Org No.): 2000729309

Sıklık: İki Aylık

eISSN: 1303-6130

pISSN: 1300-0527

Sayı

Yazarlar:

Durmuş ÖZDEMİR and Betül ÖZTÜRK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Chemistry 2004 Vol.28 Issue 4, pp.497-514

Belge Tipi:

Makale

Yayın Tarihi:

3/2004

Belge Dili:

Türkçe

Document ID (Org No.):

2000729309

Sıklık:

İki Aylık

eISSN:

1303-6130

pISSN:

1300-0527