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Machine Learning in Heliophysics and space weather forecasting: a white paper of finding and recommendations
- Source :
- SAO/NASA Astrophysics Data System.
- Publication Year :
- 2020
- Publisher :
- United States: NASA Center for Aerospace Information (CASI), 2020.
-
Abstract
- The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology,Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers,expert modelers, and computer/data scientists. Their objective was to discuss critical developments and prospects of the application of machine and/or deep learning techniques for data analysis, modeling and forecasting in Heliophysics, and to shape a strategy for further developments in the field. The workshop combined a set of plenary sessions featuring invited introductory talks interleaved with a set of open discussion sessions. The outcome of the discussion is encapsulated in this white paper that also features a top-level list of recommendations agreed by participants
- Subjects :
- Aeronautics (General)
Subjects
Details
- Language :
- English
- Database :
- NASA Technical Reports
- Journal :
- SAO/NASA Astrophysics Data System
- Notes :
- 791926.02.03.06.44.
- Publication Type :
- Report
- Accession number :
- edsnas.20205003816
- Document Type :
- Report