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Sensors 2016, 16(6), 827; doi:10.3390/s16060827

Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

1
School of Instrumentation Science & Opto-Electronics Engineering, Beihang University, Beijing 100191, China
2
Beijing Key Laboratory for Optoelectronic Measurement Technology, Beijing Information Science & Technology University, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 11 March 2016 / Revised: 30 May 2016 / Accepted: 31 May 2016 / Published: 4 June 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [4825 KB, uploaded 4 June 2016]   |  

Abstract

One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to the spectrum of an unknown sample; the synthetic degree of grey relation coefficient is used to evaluate the similarity. A wavelength selection method based on simple-to-use interactive self-modeling mixture analysis minimizes the influence of noisy variables, and the most informative variables of the most similar samples are selected to build the multivariate calibration model based on partial least squares regression. To validate the performance of the proposed method, ultraviolet-visible absorbance spectra of mixed solutions of food coloring analytes in a concentration range of 20–200 µg/mL is measured. Experimental results show that the proposed method can not only enhance the prediction accuracy of the calibration model, but also greatly reduce its complexity. View Full-Text
Keywords: partial least squares regression; wavelength selection; multivariate calibration; ultraviolet-visible absorbance spectra; local algorithm partial least squares regression; wavelength selection; multivariate calibration; ultraviolet-visible absorbance spectra; local algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chang, H.; Zhu, L.; Lou, X.; Meng, X.; Guo, Y.; Wang, Z. Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration. Sensors 2016, 16, 827.

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