系统由拉曼光谱检测、汽油拉曼光谱数据的预处理、汽油辛烷值预测模型组成。
The system consisted of on-line detection, data pre-processing, and calculate model of gasoline octane number.
采用傅立叶变换近红外(NIR)光谱法建立了烟草中钙含量的NIR数学预测模型。
A mathematical prediction model of calcium in tobacco with FT-NIR spectrometry was established.
使用安体舒通粉末药品的近红外漫反射光谱数据建立人工神经网络模型，预测未知样品。
A real data set from near -infrared diffuse reflectance spectra of spironolactone pharmaceutical powder was used to built up an artificial neural network model to predict unknown samples.
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