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P1.20: Guedes dos Santos, Luiz Fernando
Luiz Fernando Guedes dos Santos (CUA/GSFC)
Teresa Nieves-Chinchilla (CUA / GSFC)
Barbara J Thompson (NASA/GSFC)
Michael S Kirk (NASA/GSFC)

Theme: Machine Learning in Astronomy
Title: Analyzing WIND data using machine learning

Coronal mass ejections (CMEs) are large-scale explosions of magnetic field and plasma from the Sun's corona and the primary drivers of terrestrial space weather. The fastest CMEs can reach Earth in 1-5 days expanding in size as they travel due to their strong entrained magnetic fields. Multiple viewpoint and observations require many assumptions to model the 3D CME dynamic and kinematic evolution. Although in-situ the measurements provide us great advance in how CMEs are and evolve, it still needs many assumptions to model it. Using data from Earth-directed ICME events and developing methodologies using Machine Learning techniques we expect to improve the analysis of all this data already available and search for relations not yet observed. New methods can improve categorization, relationships between quantities and evolution of the CMEs itself.

Link to PDF (may not be available yet): P1-20.pdf