SOURCE-LINKED INTELLIGENCE

Active Region Classification and Flare Forecasting

CORDIS · observation · Publication date unknown

cally, to better forecast space weather. The Active Region Classification and Flare Forecasting (ARCAFF) project will develop a beyond state-of-the-art flare forecasting system utilising end-to-end deep learning (DL) models to significantly improve upon traditional flare forecasting capabilities. ARCAFF will increase the accuracy and timeliness of current operational flare forecast products and create new time series flare forecasts. Furthermore, ARCAFF forecasts will include forecast uncertainties, another major improvement over current systems. The large amount of available space-based solar observations are an ideal candidate for this type of analysis, given DL effectiveness in modelling complex relationships. DL has already been successfully developed and deployed in weather forecasting, financial services, and health care domains, but has not been fully exploited in the solar physics domain. Solar flare forecasts from ARCAFF will be benchmarked against current systems using international community standards, and will demonstrate ARCAFF’s superior forecasting capabilities. The

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recordType

award

status

SIGNED

region

EU

value

604111.25

unit

EUR