Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification
Abstract We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based o...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-02-01
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| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2023SW003824 |
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