Published June 2019 | Version v1
Journal article

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

  • 1. Razi University, Department of Civil Engineering (Iran, Islamic Republic of)

Description

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.

Additional details

Identifiers

Publishing Information

Journal Title
Applied Water Science
Journal Volume
9
Journal Issue
4
Journal Page Range
p. 1-12
ISSN
2190-5495

INIS

Country of Publication
Germany
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
51096682
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
DRAINAGE; FROUDE NUMBER; IRRIGATION; LENGTH; SIMULATION; TRAINING; WATER; WIDTH
Descriptors DEC
DIMENSIONLESS NUMBERS; DIMENSIONS; EDUCATION; HYDROGEN COMPOUNDS; OXYGEN COMPOUNDS

Optional Information

Copyright
Copyright (c) 2019 The Author(s)