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

نویسندگان

  • Yuko Hada Muranushi
  • Takayuki Muranushi
  • Ayumi Asai
  • Daisuke Okanohara
  • Raymond H. Putra
  • Gentaro Watanabe
  • Shigeru Nemoto
  • Kazunari Shibata
چکیده

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. 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. Figure 1. A screenshot from our forecast website. The blue curve is the observed Solar X-ray Flux (1-8 Å). The red dots are our forecast of the 24-hour future maxima of the Solar X-ray Flux. The pale red curve indicates the correct prediction, in retrospect. Our ideal goal is to have all the red dots on the pale red curve.

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عنوان ژورنال:
  • CoRR

دوره abs/1606.01587  شماره 

صفحات  -

تاریخ انتشار 2016