discharge estimation of circular sewer with a combined weir-sluice gate device using artificial neural networks (anns)

 the paper presents the application of artificial neural network (ann) to determine combined weir-sluice gate device discharge relationship. the device was implemented at the brink of a typical circular sewer conduit. experimental data including hydraulic and geometric information for different amount of discharge in the sewer were used to train and validate a multilayer perceptron network. comparing result with previous studies shows that anns as a modeling tool is a bit more efficient and more accurate compare with conventional nonlinear regression statistical methods in discharge estimation of combined weir-sluice gate device.