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http://dx.doi.org/10.7464/ksct.2012.18.3.265

Rapid Characterization and Prediction of Biomass Properties via Statistical Techniques  

Cho, Hyun-Woo (Department of Industrial and Management Engineering, Daegu University)
Publication Information
Clean Technology / v.18, no.3, 2012 , pp. 265-271 More about this Journal
Abstract
The use of renewable energies has been required to diminish the dependency on fossil fuels. As one of clean energy sources biomass has been extensively studied because various biomass resources necessitated rapid characterization of their chemical and physical properties in an on-line or real-time basis. For such an analysis near-infrared (NIR) spectroscopy has been successfully applied because of its non-invasive and informative characteristics. In this work, the applicability of nonlinear chemometric techniques based on biomass near infrared (NIR) data is evaluated for the rapid prediction of ash/char contents in different types of biomass. The prediction results of various prediction models and the effect of using preprocessing methods for NIR data are compared using six types of biomass NIR data. The results showed that nonlinear prediction models yielded better prediction performance than linear ones. It also turned out that by adopting the use of proper preprocessing methods the performance of prediction of biomass properties improved.
Keywords
Renewable energy; Biomass; Nonlinear chemometric approaches; Near infrared (NIR)-based prediction with preprocessing;
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Times Cited By KSCI : 1  (Citation Analysis)
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