Prediction of pressure fluctuations on sloping stilling basins

Various types of hydraulic JUMP occurring on horizontal and sloping channels have been analyzed experimentally, theoretically, and numerically and the results are available in the literature. In this Study, artificial neural network models were developed to simulate the mean pressure fluctuations beneath a hydraulic JUMP occurring on sloping stilling basins. Multilayers feed a forward neural network with a back-propagation learning algorithm to model the pressure fluctuations beneath such a type of hydraulic jump (B-jump). An explicit formula that predicts the mean pressure fluctuation in terms of the characteristics that contribute most to the hydraulic jump occurring oil the sloping basins is presented. The proposed neural network models are compared with linear and nonlinear regession models that were developed using considered physical parameters. The results of the neural network modelling are found to be superior to the regression models and are in good agreement with the experimental results due to relatively small Values of error (mean absolute percentage error).