Research on water quality prediction of Jiangshan Port based on SCV-CBA model

Research on water quality prediction of Jiangshan Port based on SCV-CBA model

Abstract Water quality prediction is challenging due to the complex temporal oscillations inherent in time series data. This study addressed these challenges by proposing SSA-optimized CEEMDAN-VMD-CNN-BiLSTM-Attention (SCV-CBA) hybrid model to enhance prediction accuracy. The method began by decompo...

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Bibliographic Details
Main Authors: Yiting Xu, Zhaoju Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Water quality prediction
Dual decomposition
Optimization
Ablation
Generalization
Online Access:https://doi.org/10.1038/s41598-025-05708-4
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https://doi.org/10.1038/s41598-025-05708-4

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