Research on ionospheric parameters prediction based on deep learning
For ionospheric parameter prediction, the short-term and daily mean value prediction of ionospheric parameters was established by long short-term memory (LSTM) predictive neural network modeling.Two methods of point-by-point prediction and sequence prediction were utilized.Furthermore, in order to p...
Saved in:
Main Authors: | Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Department of Journal on Communications
2021-04-01
|
Series: | Tongxin xuebao |
Subjects: | |
Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021097/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Potential of Regional Ionosphere Prediction Using a Long Short‐Term Memory Deep‐Learning Algorithm Specialized for Geomagnetic Storm Period
by: Jeong‐Heon Kim, et al.
Published: (2021-09-01) -
Deep Learning for Global Ionospheric TEC Forecasting: Different Approaches and Validation
by: Xiaodong Ren, et al.
Published: (2022-05-01) -
ED‐ConvLSTM: A Novel Global Ionospheric Total Electron Content Medium‐Term Forecast Model
by: Guozhen Xia, et al.
Published: (2022-08-01) -
Forecasting Ionospheric foF2 Using Bidirectional LSTM and Attention Mechanism
by: Jun Tang, et al.
Published: (2023-11-01) -
Regional Ionospheric Parameter Estimation by Assimilating the LSTM Trained Results Into the SAMI2 Model
by: Jeong‐Heon Kim, et al.
Published: (2020-10-01)