The spectra data of the sample were completely interpreted.
并对样品的核磁氢谱和碳谱数据进行了全归属。
The structures were identified on the basis of spectra data and TLC comparison with known compounds.
应用光谱和与已知品对照TLC法鉴定了所有化合物的结构。
Nowadays there are some successful laser remote sensing spectra data analysis systems which include artificial neural network.
现在已经有了一些利用人工神经网络建立的激光遥感光谱数据的智能分析系统。
The result of testing shows that PCA laser fluorescence spectra data analysis identification model can identify spill oil effectively.
测试实验得出，PCA激光荧光光谱分析识别模型能够有效地识别溢油。
The result also shows that RBF neural network laser fluorescence spectra data analysis identification model get the best perform in velocity, the average training time is 5.547 seconds.
神经网络方面，RBF神经网络激光荧光光谱分析识别模型的速度最快，平均训练时间为5.547秒。
The result also shows that RBF neural network laser fluorescence spectra data analysis identification model get the best perform in velocity, the average training time is 5.547 seconds.
神经网络方面，RBF神经网络激光荧光光谱分析识别模型的速度最快，平均训练时间为5.547秒。
应用推荐