Machine learning assisted crustal velocity proxy: A case study over the Tibetan Plateau and its surroundings
So far only a few individuals have attempted to use Machine Learning approaches to
anticipate GPS site velocity for crustal deformation research. Generally, a dense network of …
anticipate GPS site velocity for crustal deformation research. Generally, a dense network of …
[HTML][HTML] Deep learning of GPS geodetic velocity
OM Sorkhabi, SMS Alizadeh, FT Shahdost… - Journal of Asian Earth …, 2022 - Elsevier
Installing permanent global positioning system (GPS) stations and receiving and monitoring
long-term crustal deformation requires a high cost. Another solution, which could be an …
long-term crustal deformation requires a high cost. Another solution, which could be an …
Deep learning of total electron content
OM Sorkhabi - SN Applied Sciences, 2021 - Springer
One of the most notable errors in the global navigation satellite system (GNSS) is the
ionospheric delay due to the total electron content (TEC). TEC is the number of electrons in …
ionospheric delay due to the total electron content (TEC). TEC is the number of electrons in …