• Spectroscopy and Spectral Analysis
  • Vol. 38, Issue 7, 2274 (2018)
LIU Jin, LUAN Xiao-li, and LIU Fei
Author Affiliations
  • [in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2018)07-2274-05 Cite this Article
    LIU Jin, LUAN Xiao-li, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. Spectroscopy and Spectral Analysis, 2018, 38(7): 2274 Copy Citation Text show less

    Abstract

    For the sake of the quick analysis of sodium in oil sands, near infrared spectroscopic technology was applied combing with Least Absolute Shrinkage and Selection Operator (Lasso) modeling algorithm in order to establish quantitative calibration model. The comparison with the traditional PLS modeling method was conducted for comparative analysis. The results showed that the calibration models of the sodium content established by both methods had almost the same accuracy, but the prediction performance was slightly different. The verification experiment illustrated that the model evaluation indexes of PLS and Lasso algorithms were Rp=0.998 1, RMSEP=0.010 8 and Rp=0.998 6, RMSEP=0.009 5 respectively. The effectiveness of near-infrared spectroscopic analysis to determine the sodium content in oil sands was verified. The modeling precision and applicable areas of the PLS and Lasso algorithms were compared and analyzed.
    LIU Jin, LUAN Xiao-li, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. Spectroscopy and Spectral Analysis, 2018, 38(7): 2274
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