Predicting the energy dissipation of a rough sudden expansion rectangular stilling basins using the SVM algorithm

In this research, the performance of support vector machine in predicting relativeenergy dissipation in non-prismatic channel and rough bed with trapezoidalelements has been investigated. To achieve the objectives of the present study,136 series of laboratory data are analyzed under the same laboratory conditionsusing a support vector machine. The present study entered the support vectormachine network without dimension in two different scenarios with a height of 1.50and 3.0 cm rough elements. Two statistical criteria of Root Mean Square Error andcoefficient of determination are used to evaluate the efficiency of input compounds.Hydraulically, the results show that at both heights of the rough elements, energydissipation increased with increasing Froude number. The results of the supportvector machine show that the height of the roughness element is 1.50 cm in thefirst scenario, combination number 6 with R2 = 0.990 and RMSE = 0.0129 fortraining mode and R2 = 0.993 and RMSE = 0.032 for testing mode and the heightof the roughness element 3.0 in the second scenario, combination number 6 withR2 = 0.989 and RMSE = 0.0112 for training mode, R2 = 0.994 and RMSE = 0.0224for testing mode are select as the best models. Finally, sensitivity analysis isperformed on the parameters and H / y1 parameter is selected as the most effectiveparameter.

Predicting the energy dissipation of a rough sudden expansion rectangular stilling basins using the SVM algorithm Keywords:

Relative energy dissipation , Support Vector Machine , Input parameters , Froude number