Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm
Sungrazing comets, known for their proximity to the Sun, are traditionally classified into broad groups like Kreutz, Marsden, Kracht, Meyer, and non-group comets. While existing methods successfully categorize these groups, finer distinctions within the Kreutz subgroup remain a challenge. In this...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Korean Space Science Society
2024-03-01
|
| Series: | Journal of Astronomy and Space Sciences |
| Subjects: | |
| Online Access: | https://www.janss.kr/archive/view_article?pid=jass-41-1-35 |
| _version_ | 1827283124555350016 |
|---|---|
| author | Ulkar Karimova Yu Yi |
| author_facet | Ulkar Karimova Yu Yi |
| author_sort | Ulkar Karimova |
| collection | DOAJ |
| description | Sungrazing comets, known for their proximity to the Sun, are traditionally classified into broad groups like Kreutz, Marsden,
Kracht, Meyer, and non-group comets. While existing methods successfully categorize these groups, finer distinctions within
the Kreutz subgroup remain a challenge. In this study, we introduce an automated classification technique using the densitybased
spatial clustering of applications with noise (DBSCAN) algorithm to categorize sungrazing comets. Our method extends
traditional classifications by finely categorizing the Kreutz subgroup into four distinct subgroups based on a comprehensive
range of orbital parameters, providing critical insights into the origins and dynamics of these comets. Corroborative
analyses validate the accuracy and effectiveness of our method, offering a more efficient framework for understanding the
categorization of sungrazing comets. |
| first_indexed | 2024-04-24T09:30:31Z |
| format | Article |
| id | doaj.art-f592eb41dff64b329dfc61b7c5d722a3 |
| institution | Directory Open Access Journal |
| issn | 2093-5587 2093-1409 |
| language | English |
| last_indexed | 2024-04-24T09:30:31Z |
| publishDate | 2024-03-01 |
| publisher | The Korean Space Science Society |
| record_format | Article |
| series | Journal of Astronomy and Space Sciences |
| spelling | doaj.art-f592eb41dff64b329dfc61b7c5d722a32024-04-15T14:09:46ZengThe Korean Space Science SocietyJournal of Astronomy and Space Sciences2093-55872093-14092024-03-01411354210.5140/JASS.2024.41.1.35Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering AlgorithmUlkar Karimova0https://orcid.org/0000-0003-3396-2815Yu Yi1https://orcid.org/0000-0001-9348-454XChungnam National UniversityChungnam National UniversitySungrazing comets, known for their proximity to the Sun, are traditionally classified into broad groups like Kreutz, Marsden, Kracht, Meyer, and non-group comets. While existing methods successfully categorize these groups, finer distinctions within the Kreutz subgroup remain a challenge. In this study, we introduce an automated classification technique using the densitybased spatial clustering of applications with noise (DBSCAN) algorithm to categorize sungrazing comets. Our method extends traditional classifications by finely categorizing the Kreutz subgroup into four distinct subgroups based on a comprehensive range of orbital parameters, providing critical insights into the origins and dynamics of these comets. Corroborative analyses validate the accuracy and effectiveness of our method, offering a more efficient framework for understanding the categorization of sungrazing comets.https://www.janss.kr/archive/view_article?pid=jass-41-1-35sungrazing cometssolar system originscoronagraphic observationsdensity-based spatial clustering of applications with noise (dbscan) algorithmcomet categorizationkreutz subgroups |
| spellingShingle | Ulkar Karimova Yu Yi Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm Journal of Astronomy and Space Sciences sungrazing comets solar system origins coronagraphic observations density-based spatial clustering of applications with noise (dbscan) algorithm comet categorization kreutz subgroups |
| title | Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm |
| title_full | Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm |
| title_fullStr | Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm |
| title_full_unstemmed | Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm |
| title_short | Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm |
| title_sort | classification of subgroups of solar and heliospheric observatory soho sungrazing kreutz comet group by the density based spatial clustering of applications with noise dbscan clustering algorithm |
| topic | sungrazing comets solar system origins coronagraphic observations density-based spatial clustering of applications with noise (dbscan) algorithm comet categorization kreutz subgroups |
| url | https://www.janss.kr/archive/view_article?pid=jass-41-1-35 |
| work_keys_str_mv | AT ulkarkarimova classificationofsubgroupsofsolarandheliosphericobservatorysohosungrazingkreutzcometgroupbythedensitybasedspatialclusteringofapplicationswithnoisedbscanclusteringalgorithm AT yuyi classificationofsubgroupsofsolarandheliosphericobservatorysohosungrazingkreutzcometgroupbythedensitybasedspatialclusteringofapplicationswithnoisedbscanclusteringalgorithm |