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Quantitative Prediction of High‐Energy Electron Integral Flux at Geostationary Orbit Based on Deep Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Response of geostationary communications satellite solid-state power amplifiers to high-energy electron fluence
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An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions
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Acceleration of “Seed Electrons” by Whistler Turbulence Near the Geosynchronous Orbit
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The analysis of electron fluxes at geosynchronous orbit employing a NARMAX approach
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Resonant enhancement of relativistic electron fluxes during geomagnetically active periods
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Review of radiation belt relativistic electron losses
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Studies of spacecraft charging on a geosynchronous telecommunications satellite
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Relativistic electron dynamics in the inner magnetosphere — a review
inferredcites →https://doi.org/10.1029/1999ja900444openalex-snapshot
A model for generating relativistic electrons in the Earth's inner magnetosphere based on gyroresonant wave‐particle interactions
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Quantitative prediction of radiation belt electrons at geostationary orbit based on solar wind measurements
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Outer zone relativistic electron acceleration associated with substorm‐enhanced whistler mode chorus
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Acceleration and loss of relativistic electrons during geomagnetic storms
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Variations of 0.7–6.0 MeV electrons at geosynchronous orbit as a function of solar wind
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Quantitative forecast of relativistic electron flux at geosynchronous orbit based on low‐energy electron flux
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A three‐dimensional asymmetric magnetopause model
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A neural network-based geosynchronous relativistic electron flux forecasting model
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Operational Nowcasting of Electron Flux Levels in the Outer Zone of Earth's Radiation Belt
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Recurrent geomagnetic storms and relativistic electron enhancements in the outer magnetosphere: ISTP coordinated measurements
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Coronal mass ejections, magnetic clouds, and relativistic magnetospheric electron events: ISTP
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Potential waves for relativistic electron scattering and stochastic acceleration during magnetic storms
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Relativistic theory of wave‐particle resonant diffusion with application to electron acceleration in the magnetosphere
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Effects of the Solar Wind on Magnetospheric Dynamics: Energetic Electrons at the Synchronous Orbit
inferredcites →https://doi.org/10.1029/ja095ia09p15133openalex-snapshot
Linear prediction filter analysis of relativistic electron properties at 6.6 R E
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A 27-day periodicity in outer zone trapped electron intensities
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Pitch Angle Distribution Evolution of Energetic Electrons by Whistler-Mode Chorus
inferredcites →https://doi.org/10.1109/5.58337openalex-snapshot
Backpropagation through time: what it does and how to do it
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Learning long-term dependencies with gradient descent is difficult
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Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
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FORECAST OF THE ENHANCEMENT OF RELATIVISTIC ELECTRON AT THE GEO-SYNCHRONOUS ORBIT
inferredcites →https://doi.org/10.11728/cjss2011.02.176openalex-snapshot
Prediction of Relativistic Electron Flux at Geosynchronous Orbit Based on Magnetic Field
inferredcites →https://doi.org/10.11728/cjss2012.03.354openalex-snapshot
Study on the forecasting method of relativistic electron flux at geostationary orbit based on support vector machine
inferredcites →https://doi.org/10.11728/cjss2013.04.418openalex-snapshot
Approach for Predicting the Energetic Electron Flux in Geosynchronous Earth Orbit
inferredcites →https://doi.org/10.5194/angeo-20-947-2002openalex-snapshot
Neural network prediction of relativistic electrons at geosynchronous orbit during the storm recovery phase: effects of recurring substorms
inferredcites →https://doi.org/10.5194/angeo-20-953-2002openalex-snapshot
A solar cycle of spacecraft anomalies due to internal charging
inferredcites →https://doi.org/10.5194/angeo-33-405-2015openalex-snapshot
Online NARMAX model for electron fluxes at GEO
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Short-term forecast of high-energy electron flux based on GPR
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inferred← citeshttps://doi.org/10.1029/2022sw003153openalex-snapshot
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inferred← citeshttps://doi.org/10.1029/2023sw003466openalex-snapshot
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Enhancing ≥2 MeV Electron Fluence Predictions in GEO Orbit Through Three Deep Learning Strategies
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Research Progress in High-Energy Electron Flux Prediction Methods in Geosynchronous Orbit
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Development of New Capabilities Using Machine Learning for Space Weather Prediction
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Machine Learning for the Relationship of High-Energy Electron Flux between GEO and MEO with Application to Missing Values Imputation for Beidou MEO Data
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