2016/06/06 by Hada-Muranushi, Yuko, Muranushi, Takayuki, Asai, Ayumi +5
#FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Solar and Stellar Astrophysics (astro-ph.SR)
paper · doi:10.48550/arxiv.1606.01587
Automated forecasts serve important role in space weather science, by providing statistical insights to flare-trigger mechanisms, and by enabling tailor-made forecasts and high-frequency forecasts. Only by realtime forecast we can experimentally measure the performance of flare-forecasting methods while confidently avoiding overlearning. We have been operating unmanned flare forecast service since August, 2015 that provides 24-hour-ahead forecast of solar flares, every 12 minutes. We report the method and prediction results of the system.