Surveying Machine Learning Approaches to Space Plasma Region Identification

Identifying and classifying near-Earth plasma regions is integral to understand aspects such as waves, turbulence, and magnetic reconnection. In recent years, machine learning (ML) and artificial intelligence techniques have been utilized to understand space plasma. Algorithms such as convolutional neural networks (CNNs) and self-organizing maps (SOMs) have been employed. In this work, we survey this new but nascent area of research and identify best practices for the use of ML in this scope.