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The purpose of this paper is to classify 93# and 97# gasoline by using principal component analysis (PCA) with self-organizing competitive neural network method and to establish near infrared transmission spectroscopy and reflectance spectroscopy qualitative identification model in 1100-1700nm spectral region. The spectral data is condensed by PCA method before modeling, and three principal components...
A new method for the fast discrimination of brands of Chinese distilled spirit by means of near infrared transmission spectroscopy was developed. A Field Spec 3 spectroradiometer was used for collecting 60 sample transmission and reflectance data of the three brands of Chinese distilled spirit separately. Then principal component analysis (PCA) was used to process the spectral data after pretreatment...
Pattern recognition problems specifically for spectral data were developed. As an application, classification of four tea varieties based on near infrared spectra was taken by using the method. Factor analysis (FA) and artificial neural networks (ANN) were used for pattern recognition in this research. FA is a very effective data mining way; it was applied to enhance species features and reduce data...
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