[HTML][HTML] An ionospheric TEC forecasting model based on a CNN-LSTM-attention mechanism neural network

J Tang, Y Li, M Ding, H Liu, D Yang, X Wu - Remote Sensing, 2022‏ - mdpi.com
Ionospheric forecasts are critical for space-weather anomaly detection. Forecasting
ionospheric total electron content (TEC) from the global navigation satellite system (GNSS) …

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 …

[HTML][HTML] Ionospheric TEC forecasting over an Indian low latitude location using long short-term memory (LSTM) deep learning network

KD Reddybattula, LS Nelapudi, M Moses… - Universe, 2022‏ - mdpi.com
The forecasting of ionospheric electron density has been of great interest to the research
scientists and engineers' community as it significantly influences satellite-based navigation …

LSTM-based short-term ionospheric TEC forecast model and positioning accuracy analysis

T **e, Z Dai, X Zhu, B Chen, C Ran - GPS Solutions, 2023‏ - Springer
Ionospheric delay is one of the major error sources in global navigation satellite system
(GNSS). The ionospheric delay can be corrected by empirical models, which, however, are …

An investigation of ionospheric TEC prediction maps over China using bidirectional long short‐term memory method

S Shi, K Zhang, S Wu, J Shi, A Hu, H Wu, Y Li - Space Weather, 2022‏ - Wiley Online Library
The ionospheric total electron content (TEC) is an important ionospheric parameter, and it is
widely utilized in research such as space weather prediction and precise positioning …

An approach for predicting global ionospheric TEC using machine learning

J Tang, Y Li, D Yang, M Ding - Remote Sensing, 2022‏ - mdpi.com
Accurate corrections for ionospheric total electron content (TEC) and early warning
information are crucial for global navigation satellite system (GNSS) applications under the …

Enhancing SMEs digital transformation through machine learning: A framework for adaptive quality prediction

MC Chiu, YJ Huang, CJ Wei - Journal of Industrial Information Integration, 2024‏ - Elsevier
As smart manufacturing expands, businesses see the importance of digital transformation,
especially for small and medium-sized enterprises (SMEs). Unlike larger companies, SMEs …

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 …

Machine learning based storm time modeling of ionospheric vertical total electron content over Ethiopia

A Nigusie, A Tebabal, F Feyissa - Scientific Reports, 2024‏ - nature.com
Geomagnetic storms can cause variations in the ionization levels of the ionosphere, which is
commonly studied using the total electron content (TEC). TEC is a crucial parameter to …

Seismo-ionospheric precursory detection using hybrid Bayesian-LSTM network model with uncertainty-boundaries and anomaly-intensity

M Saqib, E Şentürk, MA Adil, M Freeshah - Advances in Space Research, 2024‏ - Elsevier
Several efforts have been made to understand the complex physical processes involved in a
seismic process, but the findings are vague considering prediction capabilities …