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《Chinese Journal of Analytical Chemistry》 1993-04
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Artificial Neural Networks and Its Application in Multi-component Infrared Spectroscopic Analysis

Yin Longbiao (Department of Chemistry, East China University of Chemical Technology, Shanghai 200237)Li Zheng, Xu Li, Cheng Zhaonian (Shanghai Institute of Metallurgy, Chinese Academy of Sciences, Shanghai 200050)  
This article describes the artificial neural networks and its application in the multi-component infrared analysis. The average recoveries of infrared determination of four-component o-dichlorobenzene , m-dichlorobenzene, p-dimethyl benzene and cyclobexane were 102. 3%, 100. 3% ,101. 6% ,and 100. 0% .respec- tively. This study indicates that when nonlinear response due to component interaction or due to nonlinear instrumental response functions are present , artificial neural networks may be capable of giving superior prefor-mance for spectroscopic calibration. Thus, the artificial neural networks may provide a new approach to determine the content from multi-component infrared spectroscopic data without any preliminary chemical separation.
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