This chapter describes the state-of-the-art concerning the use of machine learning methods for solar flare prediction. The general perspective is the one of the Flare Likelihood And Region Eruption foreCASTing (FLARECAST) project, which started in 2015 within the Horizon 2020 framework. The computational aspects of this project are described, with specific focus on the mathematical properties of the algorithms implemented in the FLARECAST pipeline and on the technological services that the project is providing to the heliophysics community.
Machine learning for flare forecasting
Massone AM;Piana M
2018
Abstract
This chapter describes the state-of-the-art concerning the use of machine learning methods for solar flare prediction. The general perspective is the one of the Flare Likelihood And Region Eruption foreCASTing (FLARECAST) project, which started in 2015 within the Horizon 2020 framework. The computational aspects of this project are described, with specific focus on the mathematical properties of the algorithms implemented in the FLARECAST pipeline and on the technological services that the project is providing to the heliophysics community.File in questo prodotto:
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