4 papers
Predicting solar flares with machine learning: investigating solar cycle dependence
Xiantong Wang, Yang Chen, Gabor Toth +7
A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 ho…
Interpreting LSTM Prediction on Solar Flare Eruption with Time-series Clustering
Hu Sun, Ward Manchester, Zhenbang Jiao +2
We conduct a post hoc analysis of solar flare predictions made by a Long Short Term Memory (LSTM) model employing data in the form of Space-weather HMI Active Region Patches (SHARP…
Solar Flare Intensity Prediction with Machine Learning Models
Zhenbang Jiao, Hu Sun, Xiantong Wang +4
We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 024, 630, 1236 and 24$…
Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters
Yang Chen, Ward B. Manchester, Alfred O. Hero +7
We present several methods towards construction of precursors, which show great promise towards early predictions, of solar flare events in this paper. A data pre-processing pipeli…