Prediction and interpolation of GNSS vertical time series based on the AdaBoost method considering geophysical effects
Traditional GNSS vertical time series prediction and interpolation methods only consider time variables and have ob-vious limitations.This study takes into account the impact of geophysical effects and constructs a regression problem using temperature,atmospheric pressure,polar motion,and GNSS vertical time series data,uses the adaptive boost(AdaBoost)algorithm for modeling.To verify the prediction and interpolation performance of the model,the vertical time series from 4 GNSS stations were selected for analysis.The modeling experiment shows that compared to the Prophet model,the fitting accuracy of AdaBoost model has been improved by 35％.The prediction results indicate that within a 12 month prediction peri-od,the MAE values of the AdaBoost model at four GNSS stations are approximately 4.0～4.5 mm,and the RMSE values are approximately 5.0～6.0 mm.The interpolation experiment shows that compared to the cubic spline interpolation method,the accuracy of AdaBoost interpolation model has been improved by about 15％-28％.Our experiments have shown that the Ada-Boost model considering geophysical effects can be applied to the prediction and interpolation of GNSS vertical time series.
GNSS vertical time seriesgeophysical effectspredictioninterpolationadaptive boosting algorithm
NETL
NSTL
万方数据
