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Prediction of Dynamic Plasmapause Location Using a Neural Network

Abstract As a common boundary layer that distinctly separates the regions of high-density plasmasphere and low-density plasmatrough, the plasmapause is essential to comprehend the dynamics and variability of the inner magnetosphere. Using the machine learning framework Pytorch and high-quality Van Allen Probes data set, we develop a neural network model to predict the global dynamic variation of the plasmapause location, along with the identification of 6537 plasmapause crossing events during the period from 2012 to 2017. To ...

Guo, DeYu; Fu, Song; Xiang, Zheng; Ni, Binbin; Guo, YingJie; Feng, Minghang; Guo, JianGuang; Hu, Zejun; Gu, Xudong; Zhu, Jianan; Cao, Xing; Wang, Qi;

YEAR: 2021     DOI:

Plasmapause; neural network; Van Allen Probes; space weather forecast