Mix variational mode decomposition long short-term memory for predicting of reservoir surface displacement and deformation
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P228

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    Abstract:

    In order to improve the prediction accuracy of the displacement and deformation of YANFGHE reservoir, the displacement and deformation of non-linear and non-stationary reservoir was predicted by changing the decomposition method of VMD(variational mode decomposition) and integrating VMD and LSTM (long short-term memory). A MVMDLSTM (mixed variational mode decomposition long short-term memory) model prediction method was proposed. The reliability of the new method was analyzed by comparing different single prediction models with the combined model and different data sets. The experimental results show that the MVMDLSTM model can effectively attenuate the bias of the single prediction model and the empirical mode decomposition combination model estimation, and the prediction accuracy of the MVMDLSTM model is better, which provides an effective data decision-making for the stabilization and monitoring of the prediction and warning of the reservoir's slow sliding and creeping and other small deformations.

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History
  • Received:April 10,2023
  • Revised:June 21,2024
  • Adopted:November 29,2023
  • Online: April 03,2025
  • Published:
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