159 citations · 358 across the 11 of their papers we have counts for
11 papers
Deep Learning Based Reconstruction of Total Solar Irradiance
Yasser Abduallah, Jason T. L. Wang, Yucong Shen +3
The Earth's primary source of energy is the radiant energy generated by the Sun, which is referred to as solar irradiance, or total solar irradiance (TSI) when all of the radiation…
DeepSun: Machine-Learning-as-a-Service for Solar Flare Prediction
Yasser Abduallah, Jason T. L. Wang, Yang Nie +2
Solar flare prediction plays an important role in understanding and forecasting space weather. The main goal of the Helioseismic and Magnetic Imager (HMI), one of the instruments o…
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili +38
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicis…
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks
Hao Liu, Chang Liu, Jason T. L. Wang +1
We present two recurrent neural networks (RNNs), one based on gated recurrent units and the other based on long short-term memory, for predicting whether an active region (AR) that…
Predicting Solar Flares Using a Long Short-Term Memory Network
Hao Liu, Chang Liu, Jason T. L. Wang +1
We present a long short-term memory (LSTM) network for predicting whether an active region (AR) would produce a gamma-class flare within the next 24 hours. We consider three gamma…
Predicting Solar Flares Using SDO/HMI Vector Magnetic Data Product and Random Forest Algorithm
Chang Liu, Na Deng, Jason T. L. Wang +1
Adverse space weather effects can often be traced to solar flares, prediction of which has drawn significant research interests. The Helioseismic and Magnetic Imager (HMI) produces…