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Gene expression programming to predict the discharge coefficient in rectangular side weirs

delete2015-10-01
delete105
PRE
AI
I
Isa Ebtehaj
H
Hossein Bonakdari *
H
Hamed Azimi
A
Ali Sharifi
DOI:10.1016/j.asoc.2015.07.003delete
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摘要

摘要

En 中文
In this study, gene expression programming (GEP) is employed as a new method for estimating the side weir discharge coefficient. The accuracy of existing equations in evaluating the side weir discharge coefficient is first examined. Afterward, taking into consideration the dimensionless parameters that affect the estimation of this parameter and sensitivity analysis, five different models are presented. Coefficient determination (R-2), root mean square error (RMSE), mean absolute relative error (MARE), scatter index (SI) and BIAS are used for measuring the models' performance. Two sets of experimental data are applied to evaluate the models. According to the results obtained indicate that the model with Froude number (F-1), dimensionless weir length (b/B), ratio of weir length to depth of upstream flow (b/y(1)), and ratio of weir height to its length (P/y(1)) parameters of R-2 = 0.947, MARE = 0.05, RMSE = 0.037, BIAS = 0.01 and SI = 0.067, performed the best. Accordingly, this new equation proposed through GEP can be utilized for estimating the discharge coefficient in rectangular sharp-crested side weirs. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Discharge coefficient
Gene expression programming (GEP)
Sensitivity analysis
Side weir
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期刊

Applied Soft Computing 封面图
Applied Soft Computing
IF:
6.6
论文数:
1.4W
被引数:
4.8W

机构

R
Razi University
学者数:
3.1K
论文数: 3.3K
被引数: 2.8K
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