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

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