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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 494-495Support Vector Regression on Near-Infrared Spectra...

Support Vector Regression on Near-Infrared Spectra Analysis for Moisture Determination in Lignitic Coal Samples

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Abstract:

We studied rapid moisture determination in lignitic coal samples using near-infrared (NIR) spectrometry technique. This research applied support vector regression (SVR) and discrete wavelet transform (DWT) to analyze NIR spectra. Firstly, NIR spectra were pre-processed by DWT for fitting and compression. Then, DWT coefficients were used to build support vector regression model. Through parameters optimization, the results show that DWT-SVR can obtain satisfactory performance for moisture determination in lignitic coal samples.

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Periodical:

Applied Mechanics and Materials (Volumes 494-495)

Pages:

964-967

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.494-495.964

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Online since:

February 2014

Authors:

Xiao Li Yang*, Yan Fang Li, Xing Wang Zhang, Shi Qiang Hu

Keywords:

Lignitic Coal, Moisture, Support Vector Regression (SVR)

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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