光谱学与光谱分析 |
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Variable Selection Methods Combined with Local Linear Embedding Theory Used for Optimization of Near Infrared Spectral Quantitative Models |
HAO Yong1, SUN Xu-dong1, YANG Qiang2 |
1. College of Machanical and Electronic Engineering, East China Jiaotong University, Nanchang 330013, China 2. College of Machanical and Electronic Engineering, Rizhao Polytechnic, Rizhao 276826, China |
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Abstract Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include monte carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.
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Received: 2012-06-26
Accepted: 2012-09-10
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Corresponding Authors:
HAO Yong
E-mail: haonm@163.com
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[1] Gaydou V, Kister J, Dupuy N. Chemometrics and Intelligent Laboratory Systems, 2011, 106(2): 190. [2] Yan Hui, Han Bangxing, Wu Qiongying, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2011, 79(1): 179. [3] Lidia Esteve Agelet, David D Ellis, Susan Duvick, et al. Journal of Cereal Science, 2012, 55(2): 160. [4] Liao Yitao, Fan Yuxia, Cheng Fang. Journal of Food Engineering, 2012, 109(4): 668. [5] Shen Fei, Ying Yibing, Li Bobin, et al. Food Research International, 2011, 44(5): 1521. [6] Sinelli N, Casiraghi E, Barzaghi S, et al. Food Research International, 2011, 44(5): 1427. [7] Asmund Rinnan, Frans van den Berg, Soren Balling Engelsen. Trends in Analytical Chemistry, 2009, 28(10): 1201. [8] Cai Chenbo, Yang Hongwei, Wang Bo, et al. Vibrational Spectroscopy, 2011, 56(2), 202. [9] Mohammadreza Khanmohammadi, Amir Bagheri Garmarudi, Nafiseh Khoddami, et al. Mirochemical Journal, 2010, 95(2): 337. [10] Han Qingjuan, Wu Hailong, Cai Chenbo, et al. Analytica Chimica Acta, 2008, 612(2): 121. [11] Cai Wensheng, Li Yankun, Shao Xueguang. Chemometrics and Intelligent Laboratory Systems, 2008, 90(2): 188. [12] Soares M C U, Galvao R K H, Araujo M C U, et al. Analytica Chimica Acta, 2011, 689(1): 22. [13] Liu Fei, He Yong. Food Chemistry, 2009, 115(4): 1430. [14] Hou Chenping, Wang Jing, Wu Yi, et al. Neurocomputing, 2009, 72(12): 2368. [15] Kalivas J H. Chemometrics and Intelligent Laboratory Systems, 1997, 37(2): 255. [16] Dyrby M, Engelsen S B,Nrgaard L, et al. Applied Spectroscopy, 2002, 56(5): 579. [17] Shao Xueguang, Ma Chaoxiong. Chemometrics and Intelligent Laboratory Systems, 2003, 69(1): 157. |
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