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

Research article (Journal of Hydrology, 2021) · cited 211× · AI/ML
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Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting

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Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting is a scholarly article[1].

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  • Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting. Retrieved May 24, 2026, from https://4ort.xyz/entity/coupling-a-hybrid-cnn-lstm-deep-learning-model-with-a-boundary-corrected-maximal-overlap-discrete-wavelet-transform-for-
MLA “Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/coupling-a-hybrid-cnn-lstm-deep-learning-model-with-a-boundary-corrected-maximal-overlap-discrete-wavelet-transform-for-.
BibTeX @misc{4ortxyz_coupling-a-hybrid-cnn-lstm-deep-learning-model-with-a-boundary-corrected-maximal-overlap-discrete-wavelet-transform-for-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting}}, year = {2026}, url = {https://4ort.xyz/entity/coupling-a-hybrid-cnn-lstm-deep-learning-model-with-a-boundary-corrected-maximal-overlap-discrete-wavelet-transform-for-}, note = {Accessed: 2026-05-24}}
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