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离散小波变换-遗传算法-交互检验法用于近红外光谱数据的高倍压缩与变量筛选
引用本文:王国庆,邵学广.离散小波变换-遗传算法-交互检验法用于近红外光谱数据的高倍压缩与变量筛选[J].分析化学,2005,33(2):191-194.
作者姓名:王国庆  邵学广
作者单位:中国科学技术大学化学系,合肥,230026
基金项目:高等学校优秀青年教师教学科研奖励计划;国家烟草专卖局资助项目
摘    要:用遗传算法(GA)与交互检验(CV)相结合建立了一种用于对近红外光谱(NIR)数据及其离散小波变换(DWT)系数进行变量筛选的方法,并应用于烟草样品中总挥发碱和总氮的同时测定。结果表明:NIR数据经DWT压缩为原始大小的3.3%时基本没有光谱信息的丢失;有效的变量筛选可以极大地减少模型中的变量个数,降低模型的复杂程度,改善预测的准确度。

关 键 词:近红外光谱  离散小波变换  变量筛选  数据压缩

A Discrete Wavelet Transform-Genetic Algorithm-Cross Validation Approach for High Ratio Compression and Variable Selection of Near-infrared Spectral Data
Wang Guoqing,Shao Xueguang.A Discrete Wavelet Transform-Genetic Algorithm-Cross Validation Approach for High Ratio Compression and Variable Selection of Near-infrared Spectral Data[J].Chinese Journal of Analytical Chemistry,2005,33(2):191-194.
Authors:Wang Guoqing  Shao Xueguang
Abstract:An approach for high ratio compression and variable selection of near-infrared (NIR) spectra is proposed. The informative variables, wavelength points or approximation coefficients of discrete wavelet transform (DWT) of NIR spectra, could be selected by combination of genetic algorithm (GA) and cross-validation (CV) procedure. These selected variables were used in the determination of total volatile alkaloids (TVA) and total nitrogen (TN) in tobaccos by partial least squares (PLS) method. It is proved that there is almost no loss of information when the spectral data are compressed to 3.3% of its original size. The method can significantly reduce the number of variables used in the prediction model, decrease the complexity of the model, and improve the predictive accuracy.
Keywords:Near-infrared spectroscopy  discrete wavelet transform  variable selection  data compression
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