Modelling and prediction of GNSS time series using GBDT, LSTM and SVM machine learning approaches
W Gao, Z Li, Q Chen, W Jiang, Y Feng - Journal of Geodesy, 2022 - Springer
Global navigation satellite system (GNSS) site coordinate time series provides essential
data for geodynamic and geophysical studies, realisation of a regional or global geodetic …
data for geodynamic and geophysical studies, realisation of a regional or global geodetic …
Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis
Z Li, T Lu, K Yu, J Wang - Remote Sensing, 2023 - mdpi.com
The global navigation satellite system (GNSS) position time series provides essential data
for geodynamic and geophysical studies. Interpolation of the GNSS position time series is …
for geodynamic and geophysical studies. Interpolation of the GNSS position time series is …
A novel multilayer perceptron-based non-meteorological parameters PWV retrieval model
Accurate and high-spatiotemporal-resolution predictions of precipitable water vapor (PWV)
play a crucial role in numerous atmospheric processes, including global navigation satellite …
play a crucial role in numerous atmospheric processes, including global navigation satellite …
Initial results of atmospheric weighted mean temperature estimation with Pangu-Weather in real-time GNSS PWV retrieval for China
L Huang, Y Wang, H Bi, G Zhu, L Liu, W Jiang - GPS Solutions, 2025 - Springer
Atmospheric weighted mean temperature (Tm) is pivotal for converting zenith wet delay
(ZWD) derived from global navigation satellite system (GNSS) signal to precipitable water …
(ZWD) derived from global navigation satellite system (GNSS) signal to precipitable water …
An efficient deep learning-based troposphere ZTD dataset generation method for massive GNSS CORS stations
Nowadays, a large number of Global Navigation Satellite System (GNSS) continuously
operating reference stations (CORS) have been established around the world, which have …
operating reference stations (CORS) have been established around the world, which have …
A deep learning-based approach for directly retrieving GNSS precipitable water vapor and its application in Typhoon monitoring
L Huang, D Lu, F Chen, H Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Global Navigation Satellite Systems (GNSSs) offer all-weather and real-time capabilities,
enabling the real-time monitoring of precipitable water vapor (PWV). Traditional methods for …
enabling the real-time monitoring of precipitable water vapor (PWV). Traditional methods for …
Machine learning-based estimation of hourly GNSS precipitable water vapour
Z Adavi, B Ghassemi, R Weber, N Hanna - Remote sensing, 2023 - mdpi.com
Water vapour plays a key role in long-term climate studies and short-term weather
forecasting. Therefore, to understand atmospheric variations, it is crucial to observe water …
forecasting. Therefore, to understand atmospheric variations, it is crucial to observe water …
Machine Learning-Based Calibrated Model for Forecast Vienna Mapping Function 3 Zenith Wet Delay
F Li, J Li, L Liu, L Huang, L Zhou, H He - Remote Sensing, 2023 - mdpi.com
An accurate estimation of zenith wet delay (ZWD) is crucial for global navigation satellite
system (GNSS) positioning and GNSS-based precipitable water vapor (PWV) inversion. The …
system (GNSS) positioning and GNSS-based precipitable water vapor (PWV) inversion. The …
A New Deep Learning-Assisted Global Water Vapor Stratification Model for GNSS Meteorology: Validations and Applications
Layer precipitable water (LPW), a water vapor product similar to precipitable water vapor
(PWV), reports partial moisture content within a specified vertical range. Compared with …
(PWV), reports partial moisture content within a specified vertical range. Compared with …
Deep neural networks for refining vertical modeling of global tropospheric delay
P Yuan, K Balidakis, J Wang, P Xia… - Geophysical …, 2025 - Wiley Online Library
Kinematic airborne platforms are becoming increasingly vital for Earth observation. They
highlight the critical need for accurate tropospheric delay corrections across varying …
highlight the critical need for accurate tropospheric delay corrections across varying …