Machine learning model development for predicting aeration efficiency through Parshall flume

Machine learning model development for predicting aeration efficiency through Parshall flume

This study compares several advanced machine learning models to obtain the most accurate method for predicting the aeration efficiency (E20) through the Parshall flume. The required dataset is obtained from the laboratory tests using different flumes fabricated in National Institute Technology Kuruk...

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Bibliographic Details
Main Authors: Sangeeta, Seyed Babak Haji Seyed Asadollah, Ahmad Sharafati, Parveen Sihag, Nadhir Al-Ansari, Kwok-Wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
aeration efficiency
parshall flume
prediction
machine learning models
Online Access:http://dx.doi.org/10.1080/19942060.2021.1922314

Internet

http://dx.doi.org/10.1080/19942060.2021.1922314

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