Predicting the Geoeffectiveness of CMEs Using Machine Learning. (arXiv:2206.11472v1 [astro-ph.SR])

Web: http://arxiv.org/abs/2206.11472

Coronal mass ejections (CMEs) are the most geoeffective space weather
phenomena, being associated with large geomagnetic storms, having the potential
to cause disturbances to telecommunication, satellite network disruptions,
power grid damages and failures. Thus, considering these storms' potential
effects on human activities, accurate forecasts of the geoeffectiveness of CMEs
are paramount. This work focuses on experimenting with different machine
learning methods trained on white-light coronagraph datasets of close to sun
CMEs, to estimate whether such a newly erupting ejection has …

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