Approximation of the Discharge Coefficient of Radial Gates Using Metaheuristic Regression Approaches

Parveen Sihag, Meysam Nouri, Hedieh Ahmadpari, Amin Seyedzadeh and Ozgur Kisi ()
Additional contact information
Parveen Sihag: Department of Civil Engineering, Chandigarh University, Punjab 43521-15862, India
Meysam Nouri: Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia 57561-51818, Iran
Hedieh Ahmadpari: Department of Irrigation and Reclamation Engineering, College of Aburaihan, University of Tehran, Tehran 57561-51818, Iran
Amin Seyedzadeh: Department of Water Engineering, Faculty of Agriculture, Fasa University, Fasa 57561-51818, Iran
Ozgur Kisi: Department of Civil Engineering, Technical University of Lübeck, 23562 Lübeck, Germany

Sustainability, 2022, vol. 14, issue 22, 1-21

Abstract: Radial gates are widely used for agricultural water management, flood controlling, etc. The existence of methods for the calculation of the discharge coefficient ( C d ) of such gates are complex and they are based on some assumptions. The development of new usable and simple models is needed for the prediction of C d . This study investigates the viability of a metaheuristic regression method, the Gaussian Process (GP), for the determination of the discharge coefficient of radial gates. For this purpose, a total of 2536 experimental data were compiled that cover a wide range of all the effective parameters. The results of GP were compared with the Group Method of Data Handling (GMDH), Multivariate Adaptive Regression Splines (MARS), and linear and nonlinear regression models for predicting C d of radial gates in both free-flow and submerged-flow conditions. The results revealed that the radial basis function-based GP model performed the best in free-flow condition with a Correlation Coefficient (CC) of 0.9413 and Root Mean Square Error (RMSE) of 0.0190 while the best accuracy was obtained from the Pearson VII kernel function-based GP model for the submerged flow condition with a CC of 0.9961 and RMSE of 0.0132.

Keywords: gates; submerged flow; free-flow; discharge coefficient; estimation models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/22/15145/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/22/15145/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:22:p:15145-:d:973610

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().