Adopting the Method of Principal Components Analysis Combined with Correlation Coefficient to Increase the Predicted Concentration’s Accuracy of Benzene and Its Homology Mixture
WU Zhong-chen1, XU Xiao-xuan1, YANG Ren-jie1, YU Gang2, ZHANG Cun-zhou1
1. The Photonics Center of the Physics Institute, Nankai University, Tianjin 300071, China 2. Dupont Display, California, USA; Visiting Professor of Nankai University, Tianjin 300071, China
Abstract：The concentrations of benzene and its homology mixture were measured by near infrared spectra, and the emphasis was put on the character of the principal component and its physical significance. It is pointed out that the anterior principal components are very similar to the correlation coefficient of the multi-component solution and the theoretical proof for the right condition is given. The high frequency noise of the system can be checked out by principal component combined with the correlation coefficient. Removing the noise can greatly increase the accuracy of the prediction model.
Key words：The principal component;Noise;Partial least-squares regression;Correlation coefficient;Near infrared spectrum;Benzene;Homologue
武中臣1，徐晓轩1，杨仁杰1，俞 钢2，张存洲1 . 采用主成分分析结合相关系数法提高苯及其同系物含量预测结果的准确度 [J]. 光谱学与光谱分析, 2004, 24(12): 1566-1570.
WU Zhong-chen1, XU Xiao-xuan1, YANG Ren-jie1, YU Gang2, ZHANG Cun-zhou1 . Adopting the Method of Principal Components Analysis Combined with Correlation Coefficient to Increase the Predicted Concentration’s Accuracy of Benzene and Its Homology Mixture . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2004, 24(12): 1566-1570.
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