The INT Search for Metal-Poor Stars: Spectroscopic Observations and Classification via Artificial Neural Networks-Reference-Cited by-同舟云学术

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The INT Search for Metal-Poor Stars: Spectroscopic Observations and Classification via Artificial Neural Networks

Published:2000-09 Issue:3 Volume:120 Page:1516-1531
ISSN:0004-6256
Container-title:The Astronomical Journal
language:
Short-container-title:

Author:

Allende Prieto Carlos,Rebolo Rafael,López Ramón J. García,Serra-Ricart Miquel,Beers Timothy C.,Rossi Silvia,Bonifacio Piercarlo,Molaro Paolo

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

Link

http://stacks.iop.org/1538-3881/120/i=3/a=1516/pdf

Reference32 articles.

1. Anthony-Twarog, B. J., Sarajedini, A., Twarog, B. A. & Beers, T. C. 2000, AJ, in press

2. Neural Network Classification of Stellar Spectra

3. Automated classification of stellar spectra -- II. Two-dimensional classification with neural networks and principal components analysis

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1. The Pristine survey – XIV. Chemical analysis of two ultra-metal-poor stars;Monthly Notices of the Royal Astronomical Society;2021-10-05

2. G 112-43/44: A metal-poor binary star with a unique chemical composition and Helmi stream kinematics;Astronomy & Astrophysics;2021-07

3. The R-Process Alliance: Chemodynamically Tagged Groups of Halo r-process-enhanced Stars Reveal a Shared Chemical-evolution History;The Astrophysical Journal;2021-02-01

4. The Pristine survey – V. A bright star sample observed with SOPHIE;Monthly Notices of the Royal Astronomical Society;2019-05-17

5. WIYN Open Cluster Study. LXXVI. Li Evolution Among Stars of Low/Intermediate Mass: The Metal-deficient Open Cluster NGC 2506;The Astronomical Journal;2018-03-05

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