Proposed solution for the "Save the Earth from another Carrington Event"
The Carrington Event was the most intense geomagnetic storm in recorded history, peaking from 1–2 September 1859 during solar cycle 10. It created strong auroral displays that were reported globally and caused sparking and even fires in multiple telegraph stations.
The project describes a Machine Learning approach for the Carrington Event data comprehension. We propose an innovative approach for tackling the problem of the prediction of symptoms related to possible Carrington Events, leveraging on a powerful Deep Learning Architecture. The proposed solution is based on a comparison between the data coming from the two main observatory spacecrafts actually employed, WIND and DSCOVER. It aims at improving the quality of the measurements of the DSCOVR spacecraft with a particular focus on an intelligent analysis of the solar wind behavior, by addressing a double task of "next event prediction" and "data trend analysis".