Relativistic Electron Flux Prediction at Geosynchronous Orbit Based on the Neural Network and the Quantile Regression Method

Relativistic Electron Flux Prediction at Geosynchronous Orbit Based on the Neural Network and the Quantile Regression Method

Abstract Geosynchronous satellites are exposed to the relativistic electrons, which may cause irreparable damage to the satellites. The prediction of the relativistic electron flux is therefore important for the safety of the satellites. Unlike previous works focusing on the single‐value prediction...

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Bibliographic Details
Main Authors: Hui Zhang, Suiyan Fu, Lun Xie, Duo Zhao, Chao Yue, Zuyin Pu, Ying Xiong, Tong Wu, Shaojie Zhao, Yixin Sun, Bo Cui, Zhekai Luo
Format: Article
Language:English
Published: Wiley 2020-09-01
Series:Space Weather
Subjects:
relativistic electron flux
probabilistic forecast
feedforward neural network
quantile regression
Online Access:https://doi.org/10.1029/2020SW002445
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https://doi.org/10.1029/2020SW002445

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