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 - Karimova, Ulkar; Yi, Yu (Journal of astronomy and space sciences, 2024)
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 density-based 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.