Design of radial basis function-based support vector regression in predicting the discharge coefficient of a side weir in a trapezoidal channel

Abstract

In general, trapezoidal channels are used in irrigation and drainage networks. When installing a side weir on the side wall of a trapezoidal channel, as excess water reaches the side weir plane, additional flow from the crest of the side weir is driven into the side channel. The main aim of this study is to predict the discharge coefficient of rectangular side weirs located on trapezoidal channels using support vector machines (SVMs). Based on the effective parameters on the discharge coefficient of side weirs in trapezoidal channels, six different models (SVM 1–SVM 6) are introduced. According to the analysis results of SVM 1–SVM 6 models, the superior model is introduced as a function of the Froude number (Fr), ratio of side weir length to the bottom width of a trapezoidal channel (L/b), ratio of side weir length to the flow depth upstream of the weir (L/y1), side slope of the trapezoidal channel (m) and ratio of flow depth upstream of the weir to the trapezoidal channel bottom width (y1/b). Based on the simulation results, the superior model has a reasonable accuracy. For example, the root mean square error, mean absolute relative error and correlation coefficient (R2) values calculated for the superior training model are 0.0156, 0.0327 and 0.884, respectively. Furthermore, the ratio of side weir length to trapezoidal channel bottom width (L/b) is identified as the most effective input parameter for modeling discharge coefficient. Additionally, a matrix is presented for superior model to estimate discharge coefficient of the side weirs.