Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Comparison of Models

Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Comparison of Models

Abstract We screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES‐13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting....

Full description

Saved in:
Bibliographic Details
Main Authors: L. E. Simms, N. Yu. Ganushkina, M. Van derKamp, M. Balikhin, M. W. Liemohn
Format: Article
Language:English
Published: Wiley 2023-05-01
Series:Space Weather
Subjects:
ARMAX
recurrent neural network
logistic regression
electron flux prediction
precision recall curve
ROC curve
Online Access:https://doi.org/10.1029/2022SW003263
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1029/2022SW003263

Similar Items