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Automated forecasts serve important role in space weather science, byproviding statistical insights to flare-trigger mechanisms, and by enablingtailor-made forecasts and high-frequency forecasts. Only by realtime forecastwe can experimentally measure the performance of flare-forecasting methodswhile confidently avoiding overlearning.  We have been operating unmanned flare forecast service since August, 2015that provides 24-hour-ahead forecast of solar flares, every 12 minutes. Wereport the method and prediction results of the system.

A Deep-Learning Approach for Operation of an Automated Realtime Flare Forecast