GNSS 电离层监测研究进展与展望
姚宜斌， 高鑫 - 武汉大学学报(信息科学版), 2022 - ch.whu.edu.cn
电离层作为近地空间环境的重要组成部分, 对电波通信, 卫星导航定位等都有重要影响.
监测电离层形态结构有助于对电离层时空演化特征的理解及其建模和预测 …
监测电离层形态结构有助于对电离层时空演化特征的理解及其建模和预测 …
[HTML][HTML] Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application
Abstract Machine learning (ML) has been applied to space weather problems with
increasing frequency in recent years, driven by an influx of in-situ measurements and a …
increasing frequency in recent years, driven by an influx of in-situ measurements and a …
New findings from explainable SYM‐H forecasting using gradient boosting machines
In this work, we develop gradient boosting machines (GBMs) for forecasting the SYM‐H
index multiple hours ahead using different combinations of solar wind and interplanetary …
index multiple hours ahead using different combinations of solar wind and interplanetary …
A storm-time ionospheric TEC model with multichannel features by the spatiotemporal ConvLSTM network
X Gao, Y Yao - Journal of Geodesy, 2023 - Springer
The total electron content (TEC) is an important parameter for characterizing the morphology
of the ionosphere. Modeling the ionospheric TEC accurately during the storm time could …
of the ionosphere. Modeling the ionospheric TEC accurately during the storm time could …
[HTML][HTML] Revisiting the ground magnetic field perturbations challenge: A machine learning perspective
Forecasting ground magnetic field perturbations has been a long-standing goal of the space
weather community. The availability of ground magnetic field data and its potential to be …
weather community. The availability of ground magnetic field data and its potential to be …
Neural networks for operational SYM‐H forecasting using attention and SWICS plasma features
In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …
Deep neural networks with convolutional and LSTM layers for SYM‐H and ASY‐H forecasting
Geomagnetic indices quantify the disturbance caused by the solar activity on a planetary
scale or in particular regions of the Earth. Among them, the SYM‐H and ASY‐H indices …
scale or in particular regions of the Earth. Among them, the SYM‐H and ASY‐H indices …
Research progress and prospect of monitoring ionosphere by GNSS technique
Y YAO, X GAO - Geomatics and Information Science of Wuhan …, 2022 - ch.whu.edu.cn
Ionosphere is an important part of the near-earth space environment, and it has an important
impact on radio communication, satellite navigation and positioning. Therefore, monitoring …
impact on radio communication, satellite navigation and positioning. Therefore, monitoring …
[HTML][HTML] Heliophysics and space weather information architecture and innovative solutions: current status and ways forward
Over the past 10 years, a paradigm shift has happened in the world of science and
information technology. Open science is becoming the de facto standard, as underlined by …
information technology. Open science is becoming the de facto standard, as underlined by …
A framework for evaluating geomagnetic indices forecasting models
A Collado‐Villaverde, P Muñoz, C Cid - Space Weather, 2024 - Wiley Online Library
Abstract The use of Deep Learning models to forecast geomagnetic storms is achieving
great results. However, the evaluation of these models is mainly supported on generic …
great results. However, the evaluation of these models is mainly supported on generic …