Water Quality Prediction in Urban Waterways Based on Wavelet Packet Denoising and LSTM
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11269-024-03774-3.pdf
Reference46 articles.
1. Aloui S et al (2023) A review of Soil and Water Assessment Tool (SWAT) studies of Mediterranean catchments: Applications, feasibility, and future directions. J Environ Manage 326:116799
2. Baek SS, Pyo J, Chun JA (2020) Prediction of water level and water quality using a CNN-LSTM combined deep learning approach. Water 12(12):3399
3. Beck MB (1987) Water quality modeling: a review of the analysis of uncertainty. Water Resour Res 23(8):1393–1442
4. Brown LC, Barnwell TO (1987) The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: documentation and user manual. United States Environmental Protection Agency. https://www.researchgate.net/publication/235754236_The_enhanced_stream_water_quality_models_QUAL2E_and_QUAL2E-UNCAS_documentation_and_user_manual
5. Chen H, Zhang H (2014) Uncertainty in water quality predictions: The roles of data quality and model structure. J Hydrol 511:637–647
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