Revisiting the Ground Magnetic Field Perturbations Challenge: A Machine Learning Perspective

Revisiting the Ground Magnetic Field Perturbations Challenge: A Machine Learning Perspective

Forecasting ground magnetic field perturbations has been a long-standing goal of the space weather community. The availability of ground magnetic field data and its potential to be used in geomagnetically induced current studies, such as risk assessment, have resulted in several forecasting efforts...

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Podrobná bibliografie
Hlavní autoři: Victor A. Pinto, Amy M. Keesee, Michael Coughlan, Raman Mukundan, Jeremiah W. Johnson, Chigomezyo M. Ngwira, Hyunju K. Connor
Médium: Článek
Jazyk:English
Vydáno: Frontiers Media S.A. 2022-05-01
Edice:Frontiers in Astronomy and Space Sciences
Témata:
geomagnetically induced currents
deep learning
ground magnetic disturbance
space weather
neural network
On-line přístup:https://www.frontiersin.org/articles/10.3389/fspas.2022.869740/full

Internet

https://www.frontiersin.org/articles/10.3389/fspas.2022.869740/full

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