@article{https://doi.org/10.1029/2018SW002128,
author = {Boynton, R. J. and Amariutei, O. A. and Shprits, Y. Y. and Balikhin, M. A.},
title = {The System Science Development of Local Time-Dependent 40-keV Electron Flux Models for Geostationary Orbit},
journal = {Space Weather},
volume = {17},
number = {6},
pages = {894-906},
keywords = {radiation belts, low-energy electrons, system identification, machine learning, forecasting, ring current},
doi = {https://doi.org/10.1029/2018SW002128},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018SW002128},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018SW002128},
abstract = {Abstract At geosynchronous Earth orbit, the radiation belt/ring current electron fluxes with energies up to several hundred kiloelectron volts can vary widely in magnetic local time (MLT). This study aims to develop Nonlinear AutoRegressive eXogenous models using system science techniques, which account for the spatial variation in MLT. This is difficult for system science techniques, since there is sparse data availability of the electron fluxes at different MLT. To solve this problem, the data are binned from Geostationary Operational Environmental Satellites (GOES) 13, 14, and 15 by MLT, and a separate Nonlinear AutoRegressive eXogenous model is deduced for each bin using solar wind variables as the inputs to the model. These models are then conjugated into one spatiotemporal forecast. The model performance statistics for each model varies in MLT with a prediction efficiency between 47% and 75% and a correlation coefficient between 51.3% and 78.9% for the period from 1 March 2013 to 31 December 2017.},
year = {2019}
}