Results 151 to 158 of about 525 (158)
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A Hybrid Machine Learning Approach for Modeling Tropospheric Zenith Wet Delay with Enhanced Generalization Performance. 

Tropospheric zenith wet delay (ZWD) is one of the major error sources for space geodetic techniques and plays a vital role in meteorological research.  Accurate prior estimates for ZWD can significantly improve the performance of geodetic applications, such as precise kinematic positioning. Current single machine learning ZWD models have limitations in
Mohamed H. Sharouda   +6 more
openaire   +1 more source

Assessment of Global Forecast System–Derived Zenith Hydrostatic and Wet Delays and Systematic Bias Correction for Zenith Wet Delay over mainland China

Advances in Space Research
Junyu Li   +8 more
openaire   +1 more source

Zenith Wet Delay Retrieval Using Two Different Techniques for the South American Region and Their Comparison

International Association of Geodesy Symposia, 2014
Mattia Giovanni Crespi   +2 more
exaly  

Physical constraints for Zenith Wet Delay in Real-time Precise Point Positioning

He, S. ; https://orcid.org/0009-0003-5856-9216   +3 more
openaire   +1 more source

An inter-comparison study to estimate zenith wet delays using VLBI, GPS and NWP models

2000
Behrend, D.   +4 more
openaire   +1 more source

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