Articles | Volume 33, issue 3
https://doi.org/10.5194/angeo-33-405-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/angeo-33-405-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Online NARMAX model for electron fluxes at GEO
R. J. Boynton
CORRESPONDING AUTHOR
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
M. A. Balikhin
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
S. A. Billings
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
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Cited
32 citations as recorded by crossref.
- Electron flux models for different energies at geostationary orbit R. Boynton et al. 10.1002/2016SW001506
- Specifying High‐Altitude Electrons Using Low‐Altitude LEO Systems: The SHELLS Model S. Claudepierre & T. O'Brien 10.1029/2019SW002402
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- Complex Systems Methods Characterizing Nonlinear Processes in the Near-Earth Electromagnetic Environment: Recent Advances and Open Challenges G. Balasis et al. 10.1007/s11214-023-00979-7
- Relativistic Electron Flux Prediction at Geosynchronous Orbit Based on the Neural Network and the Quantile Regression Method H. Zhang et al. 10.1029/2020SW002445
- Challenges and Opportunities in Magnetospheric Space Weather Prediction S. Morley 10.1029/2018SW002108
- Quantitative Prediction of High‐Energy Electron Integral Flux at Geostationary Orbit Based on Deep Learning L. Wei et al. 10.1029/2018SW001829
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- NARX Neural Network Derivations of the Outer Boundary Radiation Belt Electron Flux D. Landis et al. 10.1029/2021SW002774
- System Identification of Local Time Electron Fluencies at Geostationary Orbit R. Boynton et al. 10.1029/2020JA028262
- Research Progress in High-Energy Electron Flux Prediction Methods in Geosynchronous Orbit . Ke Han et al. 10.1134/S0038094624700357
- The Influence of Solar Wind and Geomagnetic Indices on Lower Band Chorus Emissions in the Inner Magnetosphere R. Boynton et al. 10.1029/2018JA025704
- Interplanetary Parameters Leading to Relativistic Electron Enhancement and Persistent Depletion Events at Geosynchronous Orbit and Potential for Prediction V. Pinto et al. 10.1002/2017JA024902
- Global prediction of sub-relativistic and relativistic electron fluxes in the geosynchronous orbit using artificial neural networks Z. Zou et al. 10.1063/5.0245593
- Artificial neural network prediction model for geosynchronous electron fluxes: Dependence on satellite position and particle energy D. Shin et al. 10.1002/2015SW001359
- Prediction Models of ≥2 MeV Electron Daily Fluences for 3 Days at GEO Orbit Using a Long Short-Term Memory Network X. Sun et al. 10.3390/rs15102538
- Relativistic Electron Model in the Outer Radiation Belt Using a Neural Network Approach X. Chu et al. 10.1029/2021SW002808
- Space Weather Effects Produced by the Ring Current Particles N. Ganushkina et al. 10.1007/s11214-017-0412-2
- Space‐Based Sentinels for Measurement of Infrared Cooling in the Thermosphere for Space Weather Nowcasting and Forecasting M. Mlynczak et al. 10.1002/2017SW001757
- Modeling the Relationship of ≥2 MeV Electron Fluxes at Different Longitudes in Geostationary Orbit by the Machine Learning Method X. Sun et al. 10.3390/rs13173347
- The System Science Development of Local Time‐Dependent 40‐keV Electron Flux Models for Geostationary Orbit R. Boynton et al. 10.1029/2018SW002128
- Performance evaluation of SNB3GEO electrons flux forecasting model using LANL and GOES-13 observations B. Geletaw et al. 10.1016/j.asr.2022.11.044
- Real‐Time SWMF at CCMC: Assessing the Dst Output From Continuous Operational Simulations M. Liemohn et al. 10.1029/2018SW001953
- Forecasting GOES 15 >2 MeV Electron Fluxes From Solar Wind Data and Geomagnetic Indices C. Forsyth et al. 10.1029/2019SW002416
- Using ARMAX Models to Determine the Drivers of 40–150 keV GOES Electron Fluxes L. Simms et al. 10.1029/2022JA030538
- Forecast of the Energetic Electron Environment of the Radiation Belts S. Walker et al. 10.1029/2022SW003124
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- Classifier Neural Network Models Predict Relativistic Electron Events at Geosynchronous Orbit Better than Multiple Regression or ARMAX Models L. Simms & M. Engebretson 10.1029/2019JA027357
- Medium-term prediction of the fluence of relativistic electrons in geostationary orbit using solar wind streams forecast based on solar observations V. Kalegaev et al. 10.1016/j.asr.2022.08.033
- Electron Flux Dropouts at L ∼ 4.2 From Global Positioning System Satellites: Occurrences, Magnitudes, and Main Driving Factors R. Boynton et al. 10.1002/2017JA024523
- A modeling study of ≥2 MeV electron fluxes in GEO at different prediction time scales based on LSTM and transformer networks X. Sun et al. 10.1051/swsc/2024021
Latest update: 23 Feb 2025
Short summary
Data-based models have been derived to forecast the >0.8MeV and >2MeV electron fluxes at geostationary Earth orbit. The models employ solar wind parameters as inputs to provide an estimate of the average electron flux for the following day, i.e. the 1-day-ahead forecast. The identified models are shown to provide a reliable forecast for both >0.8MeV and >2MeV electron fluxes and are capable of providing real-time warnings of when the electron fluxes will be dangerously high.
Data-based models have been derived to forecast the 0.8MeV and 2MeV electron fluxes at...