195 citations · 372 across the 6 of their papers we have counts for
6 papers
Operational solar flare prediction model using Deep Flare Net
Naoto Nishizuka, Yuki Kubo, Komei Sugiura +2
We developed an operational solar flare prediction model using deep neural networks, named Deep Flare Net (DeFN). DeFN can issue probabilistic forecasts of solar flares in two cate…
Validation of Coronal Mass Ejection Arrival-Time Forecasts by Magnetohydrodynamic Simulations based on Interplanetary Scintillation Observations
Kazumasa Iwai, Daikou Shiota, Munetoshi Tokumaru +3
Coronal mass ejections (CMEs) cause various disturbances of the space environment; therefore, forecasting their arrival time is very important. However, forecasting accuracy is hin…
Reliable Probability Forecast of Solar Flares: Deep Flare Net-Reliable (DeFN-R)
Naoto Nishizuka, Yûki Kubo, Komei Sugiura +2
We developed a reliable probabilistic solar flare forecasting model using a deep neural network, named Deep Flare Net-Reliable (DeFN-R). The model can predict the maximum classes o…
Development of a coronal mass ejection arrival time forecasting system using interplanetary scintillation observations
Kazumasa Iwai, Daikou Shiota, Munetoshi Tokumaru +3
Coronal mass ejections (CMEs) cause disturbances in the environment of the Earth when they arrive at the Earth. However, the prediction of the arrival of CMEs still remains a chall…
Verification of operational solar flare forecast: Case of Regional Warning Center Japan
Yûki Kubo, Mitsue Den, Mamoru Ishii
In this article, we discuss a verification study of an operational solar flare forecast in the Regional Warning Center (RWC) Japan. The RWC Japan has been issuing four-categorical…
Solar Flare Prediction Model with Three Machine-Learning Algorithms Using Ultraviolet Brightening and Vector Magnetogram
N. Nishizuka, K. Sugiura, Y. Kubo +3
We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 h. Machine learning is used to…