Use Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm to Identify Galaxy Cluster Members

Galaxies are important structures for studying the universe, and clusters are the physical environment of galaxies. Their study is of great significance for understanding the evolution of galaxies and the distribution of matter. Classification of galaxies into clusters is an urgent subject. How do w...

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Vydáno v:IOP conference series. Earth and environmental science Ročník 252; číslo 4; s. 42033 - 42037
Hlavní autor: Zhang, Mingrui
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 09.07.2019
Témata:
Algorithms
Classification
Clustering
Codec
Data points
Galactic clusters
Galactic evolution
Galaxy distribution
Mathematical models
Stars & galaxies
ISSN:1755-1307, 1755-1315, 1755-1315
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Abstract Galaxies are important structures for studying the universe, and clusters are the physical environment of galaxies. Their study is of great significance for understanding the evolution of galaxies and the distribution of matter. Classification of galaxies into clusters is an urgent subject. How do we classify some observed galaxy data points as clusters? How to ensure the correctness of classification? Based on the results of CoDECS numerical simulation and combining DBSCAN algorithm, this paper attempts to classify the data and compare and explain the results of the three methods. Then, based on the data of Abell 383 cluster, further comparison and analysis of the three methods were made. This research can be a basis on measuring new stars.
AbstractList Galaxies are important structures for studying the universe, and clusters are the physical environment of galaxies. Their study is of great significance for understanding the evolution of galaxies and the distribution of matter. Classification of galaxies into clusters is an urgent subject. How do we classify some observed galaxy data points as clusters? How to ensure the correctness of classification? Based on the results of CoDECS numerical simulation and combining DBSCAN algorithm, this paper attempts to classify the data and compare and explain the results of the three methods. Then, based on the data of Abell 383 cluster, further comparison and analysis of the three methods were made. This research can be a basis on measuring new stars.
Author Zhang, Mingrui
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CitedBy_id crossref_primary_10_3390_rs15020411
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crossref_primary_10_3390_biomedinformatics5030054
crossref_primary_10_1007_s11042_024_19419_x
crossref_primary_10_1155_2024_2330624
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Cites_doi 10.1142/S021988781460010X
10.1007/0-306-48096-4
10.1111/j.1365-2966.2012.20675.x
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SubjectTerms Algorithms
Classification
Clustering
Codec
Data points
Galactic clusters
Galactic evolution
Galaxy distribution
Mathematical models
Stars & galaxies
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