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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Bibliographic Details
Main Authors: Mohamed Kamel Elshaarawy, Abdelrahman Kamal Hamed
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Water Science
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Online Access:https://www.tandfonline.com/doi/10.1080/23570008.2023.2290301
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