A Hybrid Deep Learning Model for Water Quality Prediction
Water quality prediction is crucial for water environment management, playing a key role in preventing pollution and ensuring the safety of water resources. To improve prediction accuracy, this paper proposes a CEEMDAN-CNN-LSTM model enhanced by a Self-Attention mechanism. First, the Complete Ensemb...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11039781/ |
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