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Optimized machine learning models for accurate prediction of the discharge coefficient in hydraulic weirs Cover

Optimized machine learning models for accurate prediction of the discharge coefficient in hydraulic weirs

Journal of Hydrology and Hydromechanics
Volume 73 (2025): Issue 3 (September 2025)
By: Faris Belaabed,  Leila Arabet,  Kamel Goudjil and  Ahmed Ouamane  
Open Access
|Sep 2025

Authors

Faris Belaabed

bellabed.faris@univ-jijel.dz

Laboratory of Hydraulic Planning and Environment, University of Biskra, Algeria

Leila Arabet

Department of Civil and Hydraulic Engineering, Laboratory LGCE, Faculty of Sciences and Technologies, University of Jijel, Algeria

Kamel Goudjil

Department of Civil Engineering, Mohammed Cherif Messaadia University, Laboratory INFRARES, Souk-Ahras, Algeria

Ahmed Ouamane

Laboratory of Hydraulic Planning and Environment, University of Biskra, Algeria
DOI: https://doi.org/10.2478/johh-2025-0023 | Journal eISSN: 1338-4333 | Journal ISSN: 0042-790X
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Language: English
Page range: 295 - 309
Submitted on: May 11, 2025
|
Accepted on: Sep 14, 2025
|
Published on: Sep 27, 2025
Published by: Slovak Academy of Sciences, Institute of Hydrology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Machine learning,
Piano keys weir,
Discharge coefficient,
Bio-inspired algorithms,
Predictive modeling,
PyQt6 interface
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2025 Faris Belaabed, Leila Arabet, Kamel Goudjil, Ahmed Ouamane, published by Slovak Academy of Sciences, Institute of Hydrology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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