Optimization model for GNSS vertical deformation prediction constrained by environmental factor characteristics

doi:10.13474/j.cnki.11-2246.2026.0213

Abstract

Abstract: In the traditional time series analysis process,the impact of environmental factors on prediction performance is often overlooked,which limits the model's prediction accuracy.Considering the influence of environmental factors on the vertical deformation of GNSS stations,a BiLSTM model optimized by the VMD and GOOSE algorithms and constrained by environmental factor characteristics is developed.Through experimental comparison,data from 14 GNSS stations between 2006 and 2019 are selected,and prediction accuracy is evaluated using the WQE index.The results show that the average WQE of the VMD-GOOSE-Ef-BiLSTM model is reduced by 84.2%,66.2%,and 50.2%compared to the BiLSTM,VMD-BiLSTM,and VMD-Ef-BiLSTM models,respectively.This demonstrates that the proposed model has higher prediction accuracy and stronger robustness.The experimental results indicate that the proposed model exhibits significant adaptability and accuracy in GNSS vertical deformation prediction,providing effective technical support for surface deformation monitoring.

Key words: environmental factors, vertical deformation, optimization model, deformation prediction

CLC Number:

P228

ZHANG Yongqi, XIAO Haiping. Optimization model for GNSS vertical deformation prediction constrained by environmental factor characteristics[J]. Bulletin of Surveying and Mapping, 2026, 0(2): 81-86,125.

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