6 papers
Daily Predictions of F10.7 and F30 Solar Indices with Deep Learning
Zhenduo Wang, Yasser Abduallah, Jason T. L. Wang +6
The F10.7 and F30 solar indices are the solar radio fluxes measured at wavelengths of 10.7 cm and 30 cm, respectively, which are key indicators of solar activity. F10.7 is valuable…
Predicting Associations between Solar Flares and Coronal Mass Ejections Using SDO/HMI Magnetograms and a Hybrid Neural Network
Jialiang Li, Vasyl Yurchyshyn, Jason T. L. Wang +6
Solar eruptions, including flares and coronal mass ejections (CMEs), have a significant impact on Earth. Some flares are associated with CMEs, and some flares are not. The associat…
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model
Jialiang Li, Vasyl Yurchyshyn, Jason T. L. Wang +6
We present a novel deep generative model, named GenMDI, to improve the temporal resolution of line-of-sight (LOS) magnetograms of solar active regions (ARs) collected by the Michel…
Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model
Hongyang Zhang, Ju Jing, Jason T. L. Wang +6
We present a transformer model, named DeepHalo, to predict the occurrence of halo coronal mass ejections (CMEs). Our model takes as input an active region (AR) and a profile, where…
Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning
Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang +6
The application of machine learning to the study of coronal mass ejections (CMEs) and their impacts on Earth has seen significant growth recently. Understanding and forecasting CME…
A Deep Learning Approach to Operational Flare Forecasting
Yasser Abduallah, Jason T. L. Wang
Solar flares are explosions on the Sun. They happen when energy stored in magnetic fields around solar active regions (ARs) is suddenly released. In this paper, we present a transf…