光谱学与光谱分析 |
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Study on Building MLR Model Using Orthogonal Signal Correction |
ZHANG Xian, YUAN Hong-fu*, GUO Zheng, SONG Chun-feng, LI Xiao-yu, XIE Jin-chun |
Beijing University of Chemical Technology, Beijing 100029, China |
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Abstract MLR and PLS models with or without OSC were studied through establishing quantitative calibration models for the peanut oil content in blending edible oils, and for the dimethylsulfoxide concentration in water solution. The cross validation results and the predication results of MLR models, were compared to evaluate the effectiveness of OSC for improving the performance of MLR model. The results show that the SEC or SEP of MLR models using OSC gets smaller. Selecting appropriate wavelengths combination by CARS method, prediction capacity of MLR model using OSC is better than PLS1 model using raw spectrum.
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Received: 2010-12-06
Accepted: 2011-03-10
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Corresponding Authors:
YUAN Hong-fu
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[1] Wold S, Antti H, Lindgren R, et al. Chelnometrics and Intelligent Laboratory Systems, 1998, 44: 175. [2] Bertran E, Iturriaga H, Maspoch S, et al. Analytica Chimica Acta, 2001, 431: 303. [3] YU Hao, CHENG Yi-yu, QU Hai-bin(余 浩,程翼宇,瞿海斌). Pretreating Near-infrared Spectra by Orthogonal Signal Correction(基于正交信号校正算法的近红外光谱预处理). Hangzhou:Zhejiang University(杭州:浙江大学), 2004. [4] LI Hongdong,Liang Yingzeng,Xu Qingsong,et al. Analytica Chimica Acta, 2009, 648: 77. |
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