Forecasting SYM‐H Index: A Comparison Between Long Short‐Term Memory and Convolutional Neural Networks
Author:
Affiliation:
1. Department of Computer, Control and Management Engineering Antonio Ruberti Sapienza University of Rome Rome Italy
2. INAF‐Istituto di Astrofisica e Planetologia Spaziali Rome Italy
3. Istituto Nazionale di Geofisica e Vulcanologia Rome Italy
Publisher
American Geophysical Union (AGU)
Subject
Atmospheric Science
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020SW002589
Reference42 articles.
1. On fast and slow Earth’s magnetospheric dynamics during geomagnetic storms: a stochastic Langevin approach
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5. Forecasting of SYMH and ASYH indices for geomagnetic storms of solar cycle 24 including St. Patrick’s day, 2015 storm using NARX neural network
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