Aiming to assess the progress and current challenges on the formidable problem of the
prediction of solar energetic events since the COSPAR/International Living With a Star …

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 …

The accurate prediction of solar flares is crucial due to their risks to astronauts, space
equipment, and satellite communication systems. Our research enhances solar flare …

Physics-informed neural networks (PINNs) are machine learning models that integrate data-
based learning with partial differential equations (PDEs). In this work, for the first time we …

Solar flares are transient space weather events that pose a significant threat to space and
ground-based technological systems, making their precise and reliable prediction crucial for …

This study progresses solar flare prediction research by presenting a full-disk deep-learning
model to forecast ≧M-class solar flares and evaluating its efficacy on both central …

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 …

The Sun constantly releases radiation and plasma into the heliosphere. Sporadically, the
Sun launches solar eruptions such as flares and coronal mass ejections (CMEs). CMEs …

Many applications produce multiway data of exceedingly high dimension. Modeling such
multi-way data is important in multichannel signal and video processing where sensors …

This paper presents a post hoc analysis of a deep learning-based full-disk solar flare
prediction model. We used hourly full-disk line-of-sight magnetogram images and selected …