Hybrid GNSS time-series prediction method based on ensemble empirical mode decomposition with long short-term memory

Hybrid GNSS time-series prediction method based on ensemble empirical mode decomposition with long short-term memory

Abstract GNSS time series prediction plays a crucial role in monitoring crustal plate movements, dam deformation, and maintaining the global coordinate framework. To address the shortcomings of traditional GNSS time series prediction methods including insufficient feature selection, limited stabilit...

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Bibliographic Details
Main Authors: Yu Zhou, Xiaoxing He, Shengdao Wang, Shunqiang Hu, Xiwen Sun, Jiahui Huang
Format: Article
Language:English
Published: Springer 2025-01-01
Series:Discover Applied Sciences
Subjects:
GNSS height time series
Prediction model
EEMD
LSTM
Online Access:https://doi.org/10.1007/s42452-024-06409-9
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