Predicting discharge coefficient of triangular side orifice using ANN and GEP models

Predicting discharge coefficient of triangular side orifice using ANN and GEP models

ABSTRACTThis 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 datase...

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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
Subjects:
Side orifice
discharge coefficient
artificial neural network
gene expression programming
prediction
Online Access:https://www.tandfonline.com/doi/10.1080/23570008.2023.2290301

Internet

https://www.tandfonline.com/doi/10.1080/23570008.2023.2290301

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