Prediction of Solar Flares Using Photospheric Magnetic Field Parameters with Deep Learning
Solar flares, particularly those of the M- and X-class, have a significant impact on human life because of their potential to disrupt critical infrastructure and communication systems on Earth. Accurate prediction of solar flares is crucial for mitigating these risks, but the black-box nature of conventional deep learning models used in flare prediction limits their trustworthiness and interpretability. In this paper, we propose a new approach to solar flare prediction using photospheric magnetic field parameters or features with deep learning. To improve model interpretability, we integrate explainable artificial intelligence (XAI) techniques, including SHapley Additive exPlanations (SHA...
| Authors | Yash Chaudhary, Jason T. L. Wang, Chunhui Xu et al. |
|---|---|
| Primary category | astro-ph.SR |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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