This is the repository for our work titled "Solar Flare Prediction through Time Series Data Augmentation", which has been submitted to AGU Space Weather Journal.
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