Causality in heliophysics: magnetic fields as a bridge between the Sun's interior and the Earth's space environment
Our host star, the Sun, is a middle-aged main sequence G type star whose activity varies.
These variations are primarily governed by solar magnetic fields which are produced in the …
These variations are primarily governed by solar magnetic fields which are produced in the …
Operational prediction of solar flares using a transformer-based framework
Y Abduallah, JTL Wang, H Wang, Y Xu - Scientific reports, 2023 - nature.com
Solar flares are explosions on the Sun. They happen when energy stored in magnetic fields
around solar active regions (ARs) is suddenly released. Solar flares and accompanied …
around solar active regions (ARs) is suddenly released. Solar flares and accompanied …
Deep learning based solar flare forecasting model. II. Influence of image resolution
Due to the accumulation of solar observational data and the development of data-driven
algorithms, deep learning methods are widely applied to build a solar flare forecasting …
algorithms, deep learning methods are widely applied to build a solar flare forecasting …
Solar flare index prediction using SDO/HMI vector magnetic data products with statistical and machine-learning methods
Solar flares, especially the M-and X-class flares, are often associated with coronal mass
ejections. They are the most important sources of space weather effects, which can severely …
ejections. They are the most important sources of space weather effects, which can severely …
Research progress on solar flare forecast methods based on data-driven models
K Han, MY Yu, JF Fu, WB Ling, D Zheng… - … in Astronomy and …, 2023 - iopscience.iop.org
Eruption of solar flares is a complex nonlinear process, and the rays and high-energy
particles generated by such an eruption are detrimental to the reliability of space-based or …
particles generated by such an eruption are detrimental to the reliability of space-based or …
Fine-grained solar flare forecasting based on the hybrid convolutional neural networks
Z Deng, F Wang, H Deng, L Tan, L Deng… - The Astrophysical …, 2021 - iopscience.iop.org
Improving the performance of solar flare forecasting is a hot topic in the solar physics
research field. Deep learning has been considered a promising approach to perform solar …
research field. Deep learning has been considered a promising approach to perform solar …
Causal Attention Deep-learning Model for Solar Flare Forecasting
X Zhang, L Xu, Z Li, X Huang - The Astrophysical Journal …, 2024 - iopscience.iop.org
Solar flares originate from the sudden release of energy stored in the magnetic field of the
active region on the Sun, but the trigger for flares is still uncertain. Currently, deep-learning …
active region on the Sun, but the trigger for flares is still uncertain. Currently, deep-learning …
A comparative analysis of machine-learning models for solar flare forecasting: identifying high-performing active region flare indicators
Solar flares create adverse space weather impacting space-and Earth-based technologies.
However, the difficulty of forecasting flares, and by extension severe space weather, is …
However, the difficulty of forecasting flares, and by extension severe space weather, is …
Long-term evolution of magnetic fields in flaring Active Region NOAA 12673
During the lifetime of AR 12673, its magnetic field evolved drastically and produced
numerous large flares. In this study, using full maps of the Sun observed by the Solar …
numerous large flares. In this study, using full maps of the Sun observed by the Solar …
太阳耀斑预报深度学习建模中样本不均衡研究
周俊， 佟继周， 李云龙， 方少峰 - 空间科学学报, 2024 - cjss.ac.cn
不同等级耀斑发生的频次存在数量级上的差别, 使基于常规卷积神经网络的耀斑预报模型通常
难以捕捉M 和X 类耀斑先兆特征, 导致高等级耀斑预报精度低的问题. 本文对于这种耀斑预报中 …
难以捕捉M 和X 类耀斑先兆特征, 导致高等级耀斑预报精度低的问题. 本文对于这种耀斑预报中 …