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Deep learning-based McIntosh classification of sunspot groups

文献类型：期刊论文

作者Deng, Xue2; Yang, Yunfei2; Zhang, Xiaoli2; Feng, Song2; Dai, Wei2; Liang, Bo2; Xiong JP(熊建萍)1
刊名Astronomy and Computing
出版日期2025-10
卷号53
关键词Deep learning Multi classification McIntosh classification Sunspot groups
ISSN号2213-1337
DOI10.1016/j.ascom.2025.100995
产权排序第2完成单位
文献子类Journal article (JA) -
英文摘要Different McIntosh classes of sunspot groups are associated with the occurrence of different levels flares. Thus, accurately classifying sunspot groups is of great significance for flare prediction. In this paper, a deep learning model named SungDC is proposed for the McIntosh classification of sunspot groups. The SungDC is designed as a single multi-classifier to simultaneously perform the classification of 60 McIntosh classes. An AGCM module is incorporated to enhance its feature extraction capability. An LCFPN neck is designed to mitigate the distortion of sunspot group features, thereby improving the quality of features. A deep learning dataset sourced from SDO/HMI continuous spectral full-disk solar images was built. In addition, a region-level data rotation augmentation technique (RLR) was improved to alleviate the problem of sample imbalance. The experimental results show that the AP, AR, and AF metrics of the SungDC are 0.645, 0.586, and 0.608, respectively. The precisions of the dki, eki, ehc, dkc, ekc, and fkc sunspot groups, which are tightly associated with M- and X-class flares, are 0.905, 0.828, 0.920, 0.710, 0.711, and 0.463, respectively. It demonstrates that the multi-classification challenge posed by sunspot groups can be feasibly addressed by deep learning methodologies. This method can also serve for research on flare prediction. © 2025 Elsevier B.V.
学科主题天文学 ; 太阳与太阳系 ; 计算机科学技术 ; 人工智能
URL标识查看原文
资助项目National Natural Science Foundation of China[11763004]
语种英语
WOS记录号WOS:001560466100001
资助机构National Natural Science Foundation of China[11763004]
源URL[http://ir.ynao.ac.cn/handle/114a53/28514]  
专题云南天文台_大样本恒星演化研究组
作者单位1.Yunnan Observatories, Chinese Academy of Sciences, Kunming, 650051, China
2.Faculty of Information Engineering and Automation, Yunnan Key Laboratory of Computer Technology Application, Kunming University of Science and Technology, Yunnan, Kunming, 650500, China;
推荐引用方式
GB/T 7714		 Deng, Xue,Yang, Yunfei,Zhang, Xiaoli,et al. Deep learning-based McIntosh classification of sunspot groups[J]. Astronomy and Computing,2025,53.
APA Deng, Xue.,Yang, Yunfei.,Zhang, Xiaoli.,Feng, Song.,Dai, Wei.,...&熊建萍.(2025).Deep learning-based McIntosh classification of sunspot groups.Astronomy and Computing,53.
MLA Deng, Xue,et al."Deep learning-based McIntosh classification of sunspot groups".Astronomy and Computing 53(2025).

入库方式： OAI收割

来源：云南天文台

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