Prediction of Dynamic Plasmapause Location Using a Neural Network-Reference-Cited by-同舟云学术

Prediction of Dynamic Plasmapause Location Using a Neural Network

Published:2021-05 Issue:5 Volume:19 Page:
ISSN:1542-7390
Container-title:Space Weather
language:en
Short-container-title:Space Weather

Author:

Guo Deyu¹^ORCID,Fu Song¹^ORCID,Xiang Zheng¹^ORCID,Ni Binbin¹²^ORCID,Guo Yingjie¹^ORCID,Feng Minghang¹,Guo Jianguang³^ORCID,Hu Zejun⁴,Gu Xudong¹^ORCID,Zhu Jianan¹,Cao Xing¹^ORCID,Wang Qi¹

Affiliation:

1. Department of Space Physics School of Electronic Information Wuhan University Wuhan China

2. Chinese Academy of Sciences Center for Excellence in Comparative Planetology Hefei China

3. National Center for Space Weather Key Laboratory of Space Weather China Meteorological Administration Beijing China

4. SOA Key Laboratory for Polar Science Polar Research Institute of China Shanghai China

Funder

National Natural Science Foundation of China

Chinese Academy of Sciences

China Postdoctoral Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020SW002622

Reference69 articles.

1. MLT dependence in the relationship between plasmapause, solar wind, and geomagnetic activity based on CRRES: 1990–1991

2. A unified approach to inner magnetospheric state prediction

3. The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting

4. Space Weather in the Machine Learning Era: A Multidisciplinary Approach

5. Resonant scattering of central plasma sheet protons by multiband EMIC waves and resultant proton loss timescales

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