Reconstructing Solar Wind Profiles Associated With Extreme Magnetic Storms: A Machine Learning Approach-Reference-Cited by-同舟云学术

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Reconstructing Solar Wind Profiles Associated With Extreme Magnetic Storms: A Machine Learning Approach

Published:2021-11-24 Issue:23 Volume:48 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophysical Research Letters

Author:

Kataoka Ryuho¹²³^ORCID,Nakano Shin'ya³⁴⁵^ORCID

Affiliation:

1. National Institute of Polar Research Tachikawa Japan

2. Okinawa Institute of Science and Technology Graduate University Okinawa Japan

3. The Graduate University for Advanced Studies SOKENDAI Hayama Japan

4. The Institute of Statistical Mathematics Tachikawa Japan

5. Center for Data Assimilation Research and Applications Joint Support Center for Data Science Research Tachikawa Japan

Funder

Japan Society for the Promotion of Science

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021GL096275

Reference41 articles.

1. Energy coupling between the solar wind and the magnetosphere

2. The rudiments of a theory of solar wind/magnetosphere coupling derived from first principles

3. A 21st Century View of the March 1989 Magnetic Storm

4. Lognormal distributions and spectra of solar wind plasma fluctuations: Wind 1995-1998

5. Observational evidence of Alfvén wings at the Earth

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1. Bridging machine learning and diagnostics of the ESA LISA space mission with equation discovery via explainable artificial intelligence;Advances in Space Research;2024-07

2. Reconstruction and prediction on solar wind speed at Ll by artificial neural network and random forest methods;CHINESE J GEOPHYS-CH;2023

3. Probabilistic modelling of substorm occurrences with an echo state network;Annales Geophysicae;2023-11-21

4. Machine learning emulator for physics-based prediction of ionospheric potential response to solar wind variations;Earth, Planets and Space;2023-09-14

5. Prediction Capability of Geomagnetic Events from Solar Wind Data Using Neural Networks;The Astrophysical Journal;2023-07-21

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