Membership determination in open clusters using the DBSCAN Clustering Algorithm

In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC 2264, NGC 2682, NGC 2244, NGC 3293, NGC 6913, NGC 7142, IC 1805, NGC 6231, NGC 2243, NGC 6451, NGC 6005...

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Vydané v:	Astronomy and computing Ročník 47; s. 100826
Hlavní autori:	Raja, M., Hasan, P., Mahmudunnobe, Md, Saifuddin, Md, Hasan, S.N.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.04.2024
Predmet:	(Galaxy: ) open clusters and associations: general, individual (Stars: ) Hertzsprung–Russell and color-magnitude diagrams DBSCAN Machine learning DBSCAN (Stars: ) Hertzsprung–Russell and color-magnitude diagrams (Galaxy: ) open clusters and associations: general, individual Machine learning
ISSN:	2213-1337, 2213-1345
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