The geomagnetic Kp index is one of the most extensively used indices of geomagnetic
activity, both for scientific and operational purposes. This article reviews the properties of the …

Learning from successful applications of methods originating in statistical mechanics,
complex systems science, or information theory in one scientific field (eg, atmospheric …

The numerous recent breakthroughs in machine learning make imperative to carefully
ponder how the scientific community can benefit from a technology that, although not …

In this study, we present a method that combines a Long Short‐Term Memory (LSTM)
recurrent neural network with a Gaussian process (GP) model to provide up to 6‐hr‐ahead …

Geomagnetic indices are convenient quantities that distill the complicated physics of some
region or aspect of near‐Earth space into a single parameter. Most of the best‐known …

The solar wind‐magnetosphere system is nonlinear. The solar wind drivers of
geosynchronous electrons with energy range of 1.8–3.5 MeV are investigated using mutual …

In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …

Geomagnetic activity is often described using summary indices to summarize the likelihood
of space weather impacts, as well as when parameterizing space weather models. The …