Journal of Infrared and Millimeter Waves, Volume. 39, Issue 3, 318(2020)

A near infrared wavelength selection method based on the variable stability and population analysis

Feng ZHANG, Xiao-Jun TANG*, Ang-Xin TONG, Bin WANG, and Jing-Wei WANG
Author Affiliations
  • Xi’an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an70049, China
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    In order to improve the efficiency and performance of the analysis model, a wavelength selection method based on variable stability and population analysis (VSPA) is proposed. Firstly, the variables are divided into sample space and variable space, and the stability of variables is calculated in the sample space. According to the stability value, the variables are divided into useful variables and useless variables by weighted bootstrap sampling technology. Then, in the variable space, the frequency of each variable is calculated, and the exponential decline function is used to remove the variables with lower frequency from the useless variables. Finally, the proposed algorithm is applied to corn NIR data set to predict the starch content. The predicted root root-mean-square (RMSEP) and predicted correlation coefficient (RP) is 0.0409 and 0.9974, respectively. The variables after selection are only 2.7% of the original spectral data. It shows that the proposed variable selection method can improve the operational efficiency and prediction accuracy of the model, and is proved to be an effective variable selection method.

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    Feng ZHANG, Xiao-Jun TANG, Ang-Xin TONG, Bin WANG, Jing-Wei WANG. A near infrared wavelength selection method based on the variable stability and population analysis[J]. Journal of Infrared and Millimeter Waves, 2020, 39(3): 318

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    Paper Information

    Category: Infrared Spectroscopy and Spectral Analysis

    Received: Dec. 19, 2019

    Accepted: --

    Published Online: Jul. 7, 2020

    The Author Email: Xiao-Jun TANG (xiaojun_tang@mail.xjtu.edu.cn)

    DOI:10.11972/j.issn.1001-9014.2020.03.009

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