Spectral classification of LAMOST emission line galaxies based on machine learning methods-Reference-Cited by-同舟云学术

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Spectral classification of LAMOST emission line galaxies based on machine learning methods

Published:2023-02 Issue: Volume:99 Page:101965
ISSN:1384-1076
Container-title:New Astronomy
language:en
Short-container-title:New Astronomy

Author:

Wang Li-Li,Zheng Wen-Yan,Rong Li-Xia,Yang Guang-Jun,Zhang Jun-Liang,Xie Yan-Hong,Wang Wen-Bo,Zhao Li-Min

Publisher

Elsevier BV

Subject

Space and Planetary Science,Astronomy and Astrophysics,Instrumentation

Reference27 articles.

1. Classification parameters for the emission-line spectra of extragalactic objects;Baldwin;Publ. Astron. Soc. Pac.,1981

2. A study of the behavior of several methods for balancing machine learning training data;Batista;ACM SIGKDD Explor. Newsl.,2004

3. Automated physical classification in the SDSS DR10. A catalogue of candidate quasars;Brescia;Mon. Not. R. Astron. Soc.,2015

4. Improving the full spectrum fitting method: accurate convolution with Gauss–Hermite functions

5. Parametric Recovery of Line‐of‐Sight Velocity Distributions from Absorption‐Line Spectra of Galaxies via Penalized Likelihood

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1. Data mining techniques on astronomical spectra data – III. Association analysis;Monthly Notices of the Royal Astronomical Society;2024-06-22

2. Galaxy spectral classification and feature analysis based on convolutional neural network;Monthly Notices of the Royal Astronomical Society;2023-09-26

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