천문학회보 (The Bulletin of The Korean Astronomical Society)
- 제42권2호
- /
- Pages.61.1-61.1
- /
- 2017
- /
- 1226-2692(pISSN)
A comparison of deep-learning models to the forecast of the daily solar flare occurrence using various solar images
- Shin, Seulki (School of Space Research, Kyung Hee University) ;
- Moon, Yong-Jae (School of Space Research, Kyung Hee University) ;
- Chu, Hyoungseok (Software Policy & Research Institute)
- 발행 : 2017.10.10
초록
As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT
키워드