Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm
LIU Jin, LUAN Xiao-li*, LIU Fei
Key Laboratory for Advanced Process Control of Light Industry of Ministry of Education, Institute of Automation, Jiangnan University, Wuxi 214122, China
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.
Key words：Near infrared spectroscopy; Sodium content in oil sand; Lasso; Quantitative calibration model
刘 进，栾小丽，刘 飞. Lasso算法的油砂钠元素近红外建模[J]. 光谱学与光谱分析, 2018, 38(07): 2274-2278.
LIU Jin, LUAN Xiao-li, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2274-2278.
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