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An advanced deep learning model for predicting water quality index

Predicting a water quality index (WQI) is important because it serves as an important metric for assessing the overall health and safety of water bodies. Our paper develops a new hybrid model for predicting the WQI. The study uses a combination of a convolutional neural network (CNN), clockwork recu...

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Bibliographic Details
Main Authors: Ehteram M., Ahmed A.N., Sherif M., El-Shafie A.
Other Authors: 57113510800
Format: Article
Published: Elsevier B.V. 2025
Subjects:
Malaysia
Analysis of variance (ANOVA)
Convolutional neural networks
Learning systems
Quality assurance
Recurrent neural networks
Water management
Water quality
Convolutional neural network
Deep learning model
General linear model analysis
Health and safety
Hybrid model
Learning models
Water quality indexes
Water quality parameters
Water resources management
Waterbodies
error analysis
index method
machine learning
parameterization
variance analysis
water management
water quality
water resource
Forecasting
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