Forecasting Ionospheric foF2 Based on Deep Learning Method

Forecasting Ionospheric foF2 Based on Deep Learning Method

In this paper, a deep learning long-short-term memory (LSTM) method is applied to the forecasting of the critical frequency of the ionosphere F2 layer (foF2). Hourly values of foF2 from 10 ionospheric stations in China and Australia (based on availability) from 2006 to 2019 are used for training and...

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Bibliographic Details
Main Authors: Xiaojun Li, Chen Zhou, Qiong Tang, Jun Zhao, Fubin Zhang, Guozhen Xia, Yi Liu
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Remote Sensing
Subjects:
ionospheric foF2
neural network
long short-term memory
forecasting model
deep learning
Online Access:https://www.mdpi.com/2072-4292/13/19/3849

Internet

https://www.mdpi.com/2072-4292/13/19/3849

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