Runoff time series prediction based on hybrid models of two-stage signal decomposition methods and LSTM for the Pearl River in China

Runoff time series prediction based on hybrid models of two-stage signal decomposition methods and LSTM for the Pearl River in China

Hydrological runoff prediction is vital for water resource management. The non-linear and non-stationary runoff series and the complex hydrological features for large-scale basins make it difficult to predict. Long short-term memory (LSTM) is effective for runoff prediction but unstable for large-sc...

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Bibliographic Details
Main Authors: Zhao Guo, Qian-Qian Zhang, Nan Li, Yun-Qiu Zhai, Wen-Tao Teng, Shuang-Shuang Liu, Guang-Guo Ying
Format: Article
Language:English
Published: IWA Publishing 2023-12-01
Series:Hydrology Research
Subjects:
large-scale basin
lstm
signal decomposition
time series runoff prediction
wavelet transformation
Online Access:http://hr.iwaponline.com/content/54/12/1505

Internet

http://hr.iwaponline.com/content/54/12/1505

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