Predicting discharge coefficient of triangular side orifice using ANN and GEP models
This study utilized machine learning models to predict the discharge coefficient for a sharp-crested triangular side orifice (TSO). The chosen models were the Artificial Neural Network (ANN) and Gene Expression Programming (GEP). Development of the models was based on 570 experimental datasets, with...
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| Main Authors: | Mohamed Kamel Elshaarawy, Abdelrahman Kamal Hamed |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Water Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23570008.2023.2290301 |
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