Flare Prediction

Solar flare prediction aims to forecast the occurrence and intensity of these powerful solar eruptions, mitigating their potentially damaging effects on technological infrastructure and space operations. Current research heavily utilizes machine learning, employing diverse architectures like convolutional neural networks (CNNs), long short-term memory networks (LSTMs), and support vector machines (SVMs), often incorporating techniques to address class imbalance and improve feature selection within multivariate time series data. These advancements are improving prediction accuracy and providing insights into flare precursors, leading to more reliable space weather forecasting and enhanced risk assessment.