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A machine-learning-based electron density (MLED) model in the inner magnetosphere

QingHua Zhou YunXiang Chen FuLiang Xiao Sai Zhang Si Liu Chang Yang YiHua He ZhongLei Gao

地球与行星物理（英文）2022，Vol.6Issue(4)：350-358,9.

地球与行星物理（英文）2022，Vol.6Issue(4)：350-358,9.DOI:10.26464/epp2022036

A machine-learning-based electron density (MLED) model in the inner magnetosphere

QingHua Zhou ¹YunXiang Chen ²FuLiang Xiao ¹Sai Zhang ²Si Liu ¹Chang Yang ²YiHua He ¹ZhongLei Gao²

作者信息

1. School of Physics and Electronic Sciences,Changsha University of Science and Technology,Changsha 410114,China
2. Hunan Provincial Key Laboratory of Flexible Electronic Materials Genome Engineering,Changsha University of Science and Technology,Changsha 410114,China
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摘要

关键词

background electron density/inner magnetosphere/machine learning/Van Allen Probes observation

Key words

background electron density/inner magnetosphere/machine learning/Van Allen Probes observation

引用本文复制引用

QingHua Zhou,YunXiang Chen,FuLiang Xiao,Sai Zhang,Si Liu,Chang Yang,YiHua He,ZhongLei Gao..A machine-learning-based electron density (MLED) model in the inner magnetosphere[J].地球与行星物理（英文）,2022,6(4):350-358,9.

基金项目

This work is supported by the National Natural Science Foundation of China grants 42074198,41774194,41974212 and 42004141,Natural Science Foundation of Hunan Province 2021JJ20010,Science and Technology Innovation Program of Hunan Province 2021RC3098,and Foundation of Education Bureau of Hunan Province for Distinguished Young Scientists 20B004.All the Van Allen Probes data are publicly available at https://cdaweb.gsfc.nasa.gov/pub/data/rbsp/.The OMNI data are obtained online(https://spdf.gsfc.nasa.gov/pub/data/omni/). （https://spdf.gsfc.nasa.gov/pub/data/omni/）

地球与行星物理（英文）

OACSCDEI

ISSN：2096-3955

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