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Statistical study of auroral variability under different solar wind conditions based on classification using deep learning techniques

ZhiYuan Shang ZhongHua Yao Jian Liu LinLi Xu Yan Xu BinZheng Zhang RuiLong Guo Yuan Yu Yong Wei

地球与行星物理（英文）2025，Vol.9Issue(6)：1163-1170,8.

地球与行星物理（英文）2025，Vol.9Issue(6)：1163-1170,8.DOI:10.26464/epp2025075

Statistical study of auroral variability under different solar wind conditions based on classification using deep learning techniques

ZhiYuan Shang ¹ZhongHua Yao ¹Jian Liu ²LinLi Xu ³Yan Xu ¹BinZheng Zhang ⁴RuiLong Guo ⁵Yuan Yu ⁴Yong Wei¹

作者信息

1. Key Laboratory of Earth and Planetary Physics,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China||College of Earth and Planetary Sciences,University of Chinese Academy of Sciences,Beijing 100029,China
2. Weihai Institute for Interdisciplinary Research,Shandong University,Weihai Shandong 264200,China||SDU-ANU Joint Science College,Shandong University,Weihai Shandong 264200,China||School of Nuclear Science and Technology,University of Science and Technology of China,Hefei 230000,China
3. Anhui Province Key Laboratory of Big Data Analysis and Application,School of Computer Science and Technology,University of Science and Technology of China,Hefei 230000,China||Anhui Province Key Laboratory of Big Data Analysis and Application,School of Computer Science and Technology,State Key Laboratory of Cognitive Intelligence,Hefei 230000,China
4. Department of Earth Sciences,The University of Hong Kong,Hong Kong SAR 999077,China
5. Laboratory of Optical Astronomy and Solar-Terrestrial Environment,Institute of Space Sciences,School of Space Science and Physics,Shandong University,Weihai Shandong 264200,China
折叠

摘要

关键词

aurora classification/deep learning/user graphical interface

Key words

aurora classification/deep learning/user graphical interface

引用本文复制引用

ZhiYuan Shang,ZhongHua Yao,Jian Liu,LinLi Xu,Yan Xu,BinZheng Zhang,RuiLong Guo,Yuan Yu,Yong Wei..Statistical study of auroral variability under different solar wind conditions based on classification using deep learning techniques[J].地球与行星物理（英文）,2025,9(6):1163-1170,8.

基金项目

This study was supported by the General Program of the National Natural Science Foundation of China(Grant No.42374212)and the National Magnetic Confinement Fusion Energy Research and Development Program of China(Grant No.2024YFE03020004).We thank Zhuang Liu for developing the ConvNeXt model,the code for which can be found at https://github.com/facebookre-search/ConvNeXt.Our user GUI code can be found at https://github.com/Ryannok/auroragui/blob/main/auroragui.py.TheTHEMIS all-sky data are available through the THEMIS website athttp://themis.ssl.berkeley.edu. （Grant No.42374212）

地球与行星物理（英文）

ISSN：2096-3955

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