基于神经网络的线指数恒星大气物理参数测量方法

通过人工神经网络的方法基于Lick线指数，来进行大气物理参数的测量，对Kurucz的合成光谱进行预处理以适应最后LAMOST光谱数据的要求，以Lick线指数与对应的大气物理参数为输入，用人工神经网络进行训练，得到训练模型通过DR8光谱数据进行测试，通过调整人工神经网络的相关参数来使实验效果达到最佳。结果证明，通过线指数人工神经网络的方法来进行大气物理参数的测量是可行的。

Line Index Stellar Atmospheric Physical Parameter Measurement Based on Artificial Neural Network

By using the artificial neural network method based on the Lick line index to develop atmospheric physical parameters measurement, Kurucz synthetic spectra preprocessing was used to adapt to the requirements of the final LAMOST spectral data, Lick line index with the corresponding atmospheric physical parameter was input, and training artificial neural network was used to get the training model through DR8 spectroscopic data for testing. The artificial neural network is aimed to achieve the best experimental effect by adjusting the relevant parameters. The experimental results show that through the artificial neural network method to get the atmospheric physical parameters is feasible.