Simultaneous determination and spectra correction of air toxic organic compounds using PLS and ANN in FTIR spectroscopy

被引:8
|
作者
Li, Y [1 ]
Wang, JD [1 ]
Yuan, WQ [1 ]
机构
[1] Nanjing Univ Sci & Technol, Lab Adv Spect, Nanjing 210014, Peoples R China
来源
JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH PART A-TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING | 2000年 / 35卷 / 09期
基金
美国国家科学基金会;
关键词
multicomponent analysis; organic compound analysis; artificial neural network; partial least-squares method; FTIR; interferent;
D O I
10.1080/10934520009377063
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this paper, the residual spectra library search was used to correct the spectrum containing one interferent. Two groups of which each sample contained no or one interferent were supplied to amplify the above method. PLS was used to identify the interferents and correct the spectra, the corrected spectra information was sent into the PLS(Partial Least Squares) and ANN(Artificial Neural Network) prediction step. The concentration of each component in the unknown mixtures was determined using two different prediction method. The RSD% (mean relative standard deviation) for the two groups was calculated respectively. The prediction results of PLS and ANN was compared to illustrate which one is better in solving this problem.
引用
收藏
页码:1673 / 1691
页数:19
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