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An ISaDE algorithm combined with support vector regression for estimating discharge coefficient of W-planform weirs
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AbstractVarious shapes of weirs, such as rectangular, trapezoidal, circular, and triangular plan forms, are used to adjust and measure the flow rate in irrigation networks. The discharge coefficient (Cd) of weirs, as the key hydraulic parameter, involves the combined effects of the geometric and hydraulic parameters. It is used to compute the flow rate over the weirs. For this purpose, a hybrid ISaDE-SVR method is proposed as a hybrid model to estimate the Cd of sharp-crested W-planform weirs. ISaDE is a high-performance algorithm among other optimization algorithms in estimating the nonlinear parameters in different phenomena. The ISaDE algorithm is used to improve the performance of SVR by finding optimal values for the SVR's parameters. To test and validate the proposed model, the experimental datasets of Kumar et al. and Ghodsian were utilized. Six different input scenarios are presented to estimate the Cd. Based on the modeling results, the proposed hybrid method estimates the Cd in terms of H/P, Lw/Wmc, and Lc/Wc. For the superior method, R2, RMSE, MAPE, and δ are obtained as 0.982, 0.006, 0.612, and 0.843, respectively. The amount of improvement in comparison with GMDH, ANFIS and SVR is 3.6%, 1.2% and 1.5% in terms of R2.
Title: An ISaDE algorithm combined with support vector regression for estimating discharge coefficient of W-planform weirs
Description:
AbstractVarious shapes of weirs, such as rectangular, trapezoidal, circular, and triangular plan forms, are used to adjust and measure the flow rate in irrigation networks.
The discharge coefficient (Cd) of weirs, as the key hydraulic parameter, involves the combined effects of the geometric and hydraulic parameters.
It is used to compute the flow rate over the weirs.
For this purpose, a hybrid ISaDE-SVR method is proposed as a hybrid model to estimate the Cd of sharp-crested W-planform weirs.
ISaDE is a high-performance algorithm among other optimization algorithms in estimating the nonlinear parameters in different phenomena.
The ISaDE algorithm is used to improve the performance of SVR by finding optimal values for the SVR's parameters.
To test and validate the proposed model, the experimental datasets of Kumar et al.
and Ghodsian were utilized.
Six different input scenarios are presented to estimate the Cd.
Based on the modeling results, the proposed hybrid method estimates the Cd in terms of H/P, Lw/Wmc, and Lc/Wc.
For the superior method, R2, RMSE, MAPE, and δ are obtained as 0.
982, 0.
006, 0.
612, and 0.
843, respectively.
The amount of improvement in comparison with GMDH, ANFIS and SVR is 3.
6%, 1.
2% and 1.
5% in terms of R2.
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