Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting

Author:

Barzegar Rahim,Aalami Mohammad Taghi,Adamowski Jan

Funder

University of Tabriz

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference80 articles.

1. Calibration and validation of watershed models and advances in uncertainty analysis in TMDL studies;Ahmadisharaf;Journal of Hydrologic Engineering,2019

2. Predicting water level fluctuations in Lake Michigan-Huron using wavelet-expert system methods;Altunkaynak;Water resources management,2014

3. Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models;Barzegar;Science of the Total Environment,2017

4. Using bootstrap ELM and LSSVM models to estimate river ice thickness in the Mackenzie River Basin in the Northwest Territories;Barzegar;Canada. Journal of Hydrology,2019

5. Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model;Barzegar;Stochastic Environmental Research and Risk Assessment,2020

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