An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network-Reference-Cited by-同舟云学术

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An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network

Published:2021-10-05 Issue:14 Volume:35 Page:4695-4726
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Wang Wen-chuan,Du Yu-jin,Chau Kwok-wing,Xu Dong-mei,Liu Chang-jun,Ma Qiang

Funder

Project of key science and technology of the Henan province

Henan province university scientific and technological innovation team

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11269-021-02920-5.pdf

Reference35 articles.

1. Akbari Asanjan A, Yang T, Hsu K, Sorooshian S, Lin J, Peng Q (2018) Short-term precipitation forecast based on the PERSIANN system and LSTM recurrent neural networks. J Geophys Res Atmos 123:12543–12563. https://doi.org/10.1029/2018JD028375

2. Al-Juboori AM (2021) A hybrid model to predict monthly streamflow using neighboring rivers. Annu Flows Water Resour Manag 35:729–743. https://doi.org/10.1007/s11269-020-02757-4

3. Alcaraz R, Rieta JJ (2010) A review on sample entropy applications for the non-invasive analysis of atrial fibrillation electrocardiograms. Biomed Signal Process Control 5:1–14. https://doi.org/10.1016/j.bspc.2009.11.001

4. Alickovic E, Kevric J, Subasi A (2018) Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction. Biomed Signal Process Control 39:94–102. https://doi.org/10.1016/j.bspc.2017.07.022

5. Bai Y, Bezak N, Zeng B, Li C, Sapac K, Zhang J (2021) Daily runoff forecasting using a cascade long short-term memory model that considers different variables. Water Resour Manag 35:1167–1181. https://doi.org/10.1007/s11269-020-02759-2

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