光谱学与光谱分析 |
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Application of KPLSR Based on Line Index in Stellar Atmospheric Physical Parameter Measurement |
WANG Jie, PAN Jing-chang*, TAN Xin |
School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Weihai 264209, China |
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Abstract In the present paper, the kernel partial least squares regression (KPLSR) method was used to measure the atmospheric physical parameters (effective temperature, surface gravity, an d chemical abundance) based on the use of Lick line index. The proposed method can reduce the computation cost and achieve an ideal measure precision. At first, the Lick indices of Kurucz synthetic spectra were extracted and the kernel regression model between the Lick indices and the atmospheric physical parameters was established using the KPLSR method. Then the physical parameters of DR8 measured spectral data were computed by the kernel regression model for testing. The test results were compared with the atmospheric physical parameters provided by SEGUE SSPP and were good results. In addition, we added a signal-to-noise ratio (SNR) of 10, 20, 30, 40, 50, 70, 90 and 120 Gaussian white noise to the Kurucz spectra. And the resulting spectra of different SNR were used to test the impact of noise on the parameter measurement. The experimental results show that the kernel regression model is sensitive to noise, the higher the SNR of spectral data, the higher the prediction accuracy of the physical parameters. The method of KPLSR based on Lick line index has small amount of computation and fast training speed, which is suitable for measuring physical parameters of stellar atmosphere.
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Received: 2013-04-22
Accepted: 2013-08-11
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Corresponding Authors:
PAN Jing-chang
E-mail: pjc@sdu.edu.cn
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[1] Cui X, Zhao Y, Chu Y, et al. Research in Astron. Astrophys, 2012, 12(9): 1197. [2] Luo, A., et al. Research in Astron. Astrophys, 2012, 12(9): 1243. [3] Zhao G, et al. Research in Astron. Astrophys, 2012, 12(7): 723. [4] Kent S M. Astrophysics and Space Science, 1994, 217: 27. [5] Re Fiorentin, et al. Astronomy & Astrophysics, 2007, 467: 1373. [6] WANG Hui-wen, WU Zai-bin, MENG Jie(王惠文,吴载斌,孟 洁). Partial Least-Squares Regression-Linear and Nonlinear Methods(偏最小二乘回归的线性与非线性方法). Beijing: National Defense Industry Press(北京:国防工业出版社), 2006. 186. [7] Thomas Lilly, Uta Fritze-V Alvensleben. Astronomy & Astrophysics, 2006, 457(2): 467. [8] Guy Worthey, Faber S M, et al. The Astrophysical Journal Supplement Series, 1994, 94: 687. [9] Trager S C, Guy Worthey, et al. Astrophysical Journal Supplement Series, 1998, 116(1): 1. [10] Guy Worthey, Ottaviani D L. The Astrophysical Journal Supplement Series, 1997, 111: 377. [11] Bart M Nicola, Karen I Theron, Jeroen Lammertyn. Chemometrics and Intelligent Laboratory Systems, 2007, 85: 243. |
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