光谱学与光谱分析 |
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Line Index Stellar Atmospheric Physical Parameter Measurement Based on Artificial Neural Network |
TAN Xin1, PAN Jing-chang1*, WANG Jie1, LUO A-li2, TU Liang-ping3 |
1. School of Mechanical, Electrical & Information Engineering, Shandong University at Weihai, Weihai 264209, China 2. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China 3. School of Science, Liaoning University of Science and Technology, Anshan 144051, China |
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Abstract 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.
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Received: 2012-10-24
Accepted: 2013-02-20
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Corresponding Authors:
PAN Jing-chang
E-mail: pjc@sdu.edu.cn
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