Machine learning models for predicting geomagnetic storms across five solar cycles using Dst index and heliospheric variables

This study aims to improve the understanding of geomagnetic storms by utilizing machine learning models and analyzing several heliophysical variables, such as the interplanetary magnetic field, proton density, solar wind speed, and proton temperature. Rather than relying on traditional correlation-b...