Daily Runoff Forecasting Using Ensemble Empirical Mode Decomposition and Long Short-Term Memory

Daily Runoff Forecasting Using Ensemble Empirical Mode Decomposition and Long Short-Term Memory

Hydrological series data are non-stationary and nonlinear. However, certain data-driven forecasting methods assume that streamflow series are stable, which contradicts reality and causes the simulated value to deviate from the observed one. Ensemble empirical mode decomposition (EEMD) was employed i...

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Bibliographic Details
Main Authors: Ruifang Yuan, Siyu Cai, Weihong Liao, Xiaohui Lei, Yunhui Zhang, Zhaokai Yin, Gongbo Ding, Jia Wang, Yi Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Earth Science
Subjects:
ensemble empirical mode decomposition
long short-term memory
three gorges reservoir
runoff forecasting
streamflow series
hydrological model
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2021.621780/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2021.621780/full

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