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.
Original language | English |
---|---|
Article number | e2021SW003000 |
Journal | Space Weather |
Volume | 19 |
Issue number | 12 |
DOIs | |
Publication status | Published - Dec 2021 |
All Science Journal Classification (ASJC) codes
- Atmospheric Science