30 citations · 65 across the 4 of their papers we have counts for
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Deep Learning-Enabled Prediction of Geoeffective CMEs Using SOHO and SDO Observations
Zhaoxin Yan, Jason T. L. Wang, Haimin Wang +5
Understanding and forecasting the geoeffectiveness of a coronal mass ejection (CME) is crucial for protecting infrastructure in the near-Earth space environment and on Earth. In th…
Improved AI-generated Solar Farside Magnetograms by STEREO and SDO Data Sets and Their Release
Hyun-Jin Jeong, Yong-Jae Moon, Eunsu Park +2
Here we greatly improve Artificial Intelligence (AI)-generated solar farside magnetograms using data sets of Solar Terrestrial Relations Observatory (STEREO) and Solar Dynamics Obs…
Accelerating and Supersonic Density Fluctuations in Coronal Hole Plumes: Signature of Nascent Solar Winds
Il-Hyun Cho, Valery M. Nakariakov, Yong-Jae Moon +5
Slow magnetoacoustic waves in a static background provide a seismological tool to probe the solar atmosphere in the analytic frame. By analyzing the spatiotemporal variation of the…
2D solar wind speeds from 6 to 26 solar radii in solar cycle 24 by using Fourier filtering
Il-Hyun Cho, Yong-Jae Moon, Valery M. Nakariakov +5
Measurement of the solar wind speed near the Sun is important for understanding the acceleration mechanism of the solar wind. In this study, we determine 2D solar wind speeds from…