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Machine‐Learning Research in the Space Weather Journal: Prospects, Scope, and Limitations.

Authors :
Lugaz, Noé
Liu, Huixin
Hapgood, Mike
Morley, Steven
Source :
Space Weather: The International Journal of Research & Applications; Dec2021, Vol. 19 Issue 12, p1-2, 2p
Publication Year :
2021

Abstract

Manuscripts based on machine‐learning techniques have significantly increased in Space Weather over the past few years. We discuss which manuscripts are within the journal's scope and emphasize that manuscripts focusing purely on a forecasting technique (rather than on understanding and forecasting a phenomenon) must correspond to a substantial improvement over the current state‐of‐the‐art techniques and present this comparison. All manuscripts shall include information about data preparation, including splitting of data between training, validation and testing sets. The software and/or algorithms used for to develop the machine‐learning technique should be included in a repository at the time of submission. Comparison with published results using other methods must be presented, and uncertainties of the forecast results must be discussed. Plain Language Summary: Manuscripts based on machine‐learning techniques have significantly increased in Space Weather over the past few years. We discuss which manuscripts are within the journal's scope and emphasize that manuscripts focusing purely on a forecasting technique (rather than on understanding and forecasting a phenomenon) must correspond to a substantial improvement over the current state‐of‐the‐art techniques and present this comparison. All manuscripts shall include information about data preparation, including splitting of data between training, validation and testing sets. The software and/or algorithms used for to develop the machine‐learning technique should be included in a repository at the time of submission. Comparison with published results using other methods must be presented, and uncertainties of the forecast results must be discussed. Key Points: Manuscripts based on machine‐learning techniques have significantly increased in Space Weather over the past few yearsWe discuss which manuscripts are within the journal's scopeWe emphasize that papers focusing on a forecasting technique must present a substantial improvement and comparison over current techniques [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15394956
Volume :
19
Issue :
12
Database :
Complementary Index
Journal :
Space Weather: The International Journal of Research & Applications
Publication Type :
Academic Journal
Accession number :
154346611
Full Text :
https://doi.org/10.1029/2021SW003000