This is the repository for our work titled "Solar Flare Prediction through Time Series Data Augmentation", which has been submitted to The Astrophysical Journal Supplement Series.
download the raw data from: https://dmlab.cs.gsu.edu/solar/data/data-comp-2020/
This project includes four parts: 1. Data preprocessing (Data preparation) 2. Using different data augmentation methods to generate synthetic samples 3. Apply 3 deep learning models to evaluate the solar flare prediction in different scenarios: (1) undersampling and imbalanced data comparison (2) data augmentation and imbalanced data comparison (3) synthetic/real ratios vs performances (4) Binary classification between synthetic and real 4. Case study on a multi-class classification