Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products

Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products

In this study, we construct two kinds of data sets from distinct time periods, both comprising line-of-sight magnetograms and knowledge-informed features. We develop eight models for forecasting ≥M-class flares within 24 hr, including the image-based convolutional neural network (CNN), CNN-BiLSTM, C...

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Bibliographic Details
Main Authors: Xuebao Li, Shunhuang Zhang, Yanfang Zheng, Ting Li, Rui Wang, Yingbo Liu, Hongwei Ye, Noraisyah Mohamed Shah, Pengchao Yan, Xuefeng Li, Xiaotian Wang, Yongshang Lv, Jinfang Wei, Honglei Jin, Changtian Xiang
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Solar active regions
Solar active region magnetic fields
Neural networks
Astronomy image processing
Solar flares
Online Access:https://doi.org/10.3847/1538-4365/ade687
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https://doi.org/10.3847/1538-4365/ade687

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