Machine learning assisted crustal velocity proxy: A case study over the Tibetan Plateau and its surroundings

B Mukherjee, PK Gautam, K Sain - Journal of Asian Earth Sciences, 2024 - Elsevier
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 …

[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 …

Determination of Helmert transformation parameters for continuous GNSS networks: a case study of the Géoazur GNSS network

DT Tran, JM Nocquet, ND Luong… - Geo-spatial Information …, 2023 - Taylor & Francis
In this paper, we propose an approach to determine seven parameters of the Helmert
transformation by transforming the coordinates of a continuous GNSS network from the …

An alternative method for estimating densification point velocity based on back propagation artificial neural networks

M Güllü, İ Yilmaz, M Yilmaz, B Turgut - Studia Geophysica et Geodaetica, 2011 - Springer
Abstract The establishment of Turkish National Fundamental GPS Network (TNFGN) was
completed in 2001 and Large Scale Map and Map Information Production Regulation …

Contemporary crustal velocity field in Alpine Mediterranean area of Italy from new geodetic data

G Farolfi, C Del Ventisette - GPS solutions, 2016 - Springer
A new crustal velocity field for the Alpine Mediterranean area was determined by using a
time series spanning 6.5 years of 113 global navigation satellite system (GNSS) permanent …

A comparative study for the estimation of geodetic point velocity by artificial neural networks

M Yilmaz, M Gullu - Journal of Earth System Science, 2014 - Springer
Abstract Space geodesy era provides velocity information which results in the positioning of
geodetic points by considering the time evolution. The geodetic point positions on the …

Crustal velocity and strain rate fields in the Balearic Islands based on continuous GPS time series from the XGAIB network (2010–2013)

A Sánchez-Alzola, C Sánchez, J Giménez, P Alfaro… - Journal of …, 2014 - Elsevier
In this paper, we present a first estimation, using the GIPSY-OASIS software, of the crustal
velocity and strain rate fields in the Balearic Islands (Spain), based on continuous GPS …

[HTML][HTML] Prediction of GNSS Velocity Accuracies Using Machine Learning Algorithms for Active Fault Slip Rate Determination and Earthquake Hazard Assessment

Hİ Solak - Applied Sciences, 2024 - mdpi.com
GNSS technology utilizes satellite signals to determine the position of a point on Earth.
Using this location information, the GNSS velocities of the points can be calculated. GNSS …

Crustal velocity and strain rate fields in the Balearic Islands based on continuous GPS time series from the XGAIB network (2010-2013)

AS Alzola, C Sánchez, J Giménez, PA García… - arXiv preprint arXiv …, 2024 - arxiv.org
In this paper, we present a first estimation, using the GIPSY-OASIS software, of the crustal
velocity and strain rate fields in the Balearic Islands (Spain), based on continuous GPS …

[PDF][PDF] Impacto de explosões solares no comportamento da ionosfera e no posicionamento com GPS na região brasileira: Estudo de caso para o dia 28 de outubro de …

MT MATSUOKA, PDEO CAMARGO… - Boletim de Ciências …, 2006 - redalyc.org
RESUMO O erro devido à ionosfera nas distâncias medidas pelo GPS (Global Positioning
System) é diretamente proporcional ao conteúdo total de elétrons (TEC–Total Electron …