FLARECAST: an I4.0 technology for space weather using satellite data

TL;DR

FLARECAST is a Horizon 2020 project that developed a machine learning platform to predict solar flares and assess the impact of space data on forecasting accuracy for the space weather community.

Contribution

It introduces a technological platform integrating machine learning algorithms for solar flare prediction and data impact assessment.

Findings

Successful implementation of a flare prediction service

Quantitative evaluation of data impact on forecasting

Enhanced understanding of space data's role in predictions

Abstract

'Flare Likelihood and Region Eruption Forecasting (FLARECAST)' is a Horizon 2020 project, which realized a technological platform for machine learning algorithms, with the objective of providing the space weather community with a prediction service for solar flares. This paper describes the FLARECAST service and shows how the methods implemented in the platform allow both flare prediction and a quantitative assessment of how the information contained in the space data utilized in the analysis may impact the forecasting process.