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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국우주과학회 Journal of Astronomy and Space Sciences Journal of Astronomy and Space Sciences Vol.41 No.1
- 발행연도
- 2024.3
- 수록면
- 35 - 42 (8page)
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초록· 키워드
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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.
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