Data di Pubblicazione:
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.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Data clustering; Machine learning; Solar flare prediction; Solar flares; Supervised methods
Elenco autori:
Piana, Michele; Massone, Annamaria
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