This paper examines the use of machine learning models to reflect the spatio-temporal correlation among GNSS reference stations.

This paper examines the use of machine learning models to reflect the spatio-temporal correlation among GNSS reference stations. To form the machine learning ...

The spatio-temporal correlations between GNSS reference stations cannot be considered when using traditional interpolation methods. This paper examines the use ...

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis. Remote Sensing.

This study addresses the potential of machine learning (ML) algorithms in geophysical and geodetic research, particularly for enhancing GNSS time series ...

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis. Remote Sens. 2023, 15, 4374 ...

This study addresses the potential of machine learning (ML) algorithms in geophysical and geodetic research, particularly for enhancing GNSS time series ...

Jan 1, 2023 · This study proposes a multi-model combined forecasting method based on the XGBoost algorithm. The method constitutes a new time series as features.

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis. Zhen Li, Tieding Lu, Kegen Yu ...

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis. 2023, Remote Sensing. Extended ...