ArticleScientific reports2023
Daily flow prediction of the Huayuankou hydrometeorological station based on the coupled CEEMDAN-SE-BiLSTM model.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Prediction of the monthly river water level by using ensemble decomposition modeling.Scientific reports · 2025Article
- Phosphorus prediction in the middle reaches of the Yangtze river based on GRA-CEEMDAN-CNLSTM-DBO.Scientific reports · 2024Article
- Predicting mine water inflow volumes using a decomposition-optimization algorithm-machine learning approach.Scientific reports · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Enhancing flood forecasting accuracy, promoting rational water resource utilization and management, and mitigating river disasters all hinge on the crucial role of improving the accuracy of daily flow prediction. The coupled model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Sample Entropy (SE), and Bidirectional Long Short-Term Memory (BiLSTM) demonstrates higher stability when faced with nonlinear and non-stationary data, stronger adaptability to various types and lengths of time series data by utilizing sample entropy, and significant advantages in processing sequential data through the BiLSTM network. In this study, in the context of predicting daily flow at the Huayuankou Hydrological Station in the lower reaches of the Yellow River, a coupled CEEMDAN-SE-BiLSTM model was developed and utilized. The results showed that the CEEMDAN-SE-BiLSTM coupled model achieved the utmost accuracy in prediction and optimal fitting performance. Compared with the CEEMDAN-SE-LSTM, CEEMDAN-BiLSTM, and BiLSTM coupled models, the root mean square error (RMSE) of this model is reduced by 42.77, 182.02, and 193.71, respectively; the mean absolute error (MAE) is reduced by 37.62, 118.60, and 126.67, respectively; and the coefficient of determination (R
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