APPLICATION OF KERNEL PARTIAL LEAST SQUARE FEATURE EXTRACTION TO QUANTITATIVE ANALYSIS OF FTIR SPECTROSCOPY OF MULTI-COMPONENT GAS MIXTURE
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O657.33

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    Abstract:

    A new method for FTIR spectral quantitative analysis was presented.The new method couples kernel partial least squares(KPLS) feature extraction with support vector regression machine(SVR) to improve the quantitative analysis accuracy and speed of seven-component alkane gas mixtures composed of methane,ethane,propane,iso-butane,n-butane,iso-pentane,and n-pentane,whose feature absorption spectra are cross each other and overlapped seriously.Firstly,the KPLS was employed to extract feature components from the ...

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HAO Hui-Min, Qiao Cong-Ming, TANG Xiao-Jun, LIU Jun-Hua . APPLICATION OF KERNEL PARTIAL LEAST SQUARE FEATURE EXTRACTION TO QUANTITATIVE ANALYSIS OF FTIR SPECTROSCOPY OF MULTI-COMPONENT GAS MIXTURE[J]. Journal of Infrared and Millimeter Waves,2009,28(2):

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