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 …

Abstract The Community Coordinated Modeling Center has been leading community‐wide
space science and space weather model validation projects for many years. These efforts …

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 …

A multilayer feed‐forward neural network model has been developed to forecast> 2 MeV
electron flux at geosynchronous orbit. The model uses as input 10 consecutive days of …

We present the recent progress in upgrading a predictive model for megaelectron‐volt
(MeV) electrons inside the Earth's outer Van Allen belt. This updated model, called PreMevE …

Characterizing and modeling processes at the sun and space plasma in our solar system
are difficult because the underlying physics is often complex, nonlinear, and not well …

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with
a set of daily averaged predictor variables including previous day's flux, seed electron flux …

Time‐integral correlations are examined between the geosynchronous relativistic electron
flux index F e1. 2 and 31 variables of the solar wind and magnetosphere. An “evolutionary …

Many solar wind and magnetosphere parameters correlate with relativistic electron flux
following storms. These include relativistic electron flux before the storm; seed electron flux; …