Search Results for author:
Found 2 papers, 0 papers with code
Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification
For example, SYMHnet achieves a forecast skill score (FSS) of 0. 343 compared to the FSS of 0. 074 of a recent gradient boosting machine (GBM) method when predicting SYM-H indices (1 hour in advance) in a large storm (SYM-H = -393 nT) using 5-minute resolution data.
Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models
In this paper, we propose a new method, called DeepCME, to estimate two properties of CMEs, namely, CME mass and kinetic energy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
