Monthly Runoff Prediction Based on STL-CEEMDAN-LSTM Model

Monthly Runoff Prediction Based on STL-CEEMDAN-LSTM Model

According to the nonlinear and non-stationary characteristics of monthly runoff sequences, the quadratic decomposition method was combined with machine learning to construct a model for predicting monthly runoff. This model uses a seasonal trend decomposition procedure based on loess (STL) to decomp...

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Bibliographic Details
Main Authors: WANG Hai, SHEN Yanqing, QI Shansheng, PAN Hongzhong, HUO Jianzhen, WANG Zhance
Format: Article
Language:zho
Published: Editorial Office of Pearl River 2025-04-01
Series:Renmin Zhujiang
Subjects:
runoff prediction
upper reaches of the Yellow River
modal decomposition
neural networks for short and long-term memory
Online Access:http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2025.04.005
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