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Influence of bed deposit in the prediction of incipient sediment motion in sewers using artificial neural networks
2018
Urban Water Journal
This study investigates the performance of artificial neural networks in predicting the incipient sediment motion in sewers. Two neural network algorithms, i.e. feed forward neural network (FFNN) and radial basis function (RBF), were employed to estimate the critical velocity over varying sediment thickness, median grain size and water depth. Empirical data from five studies were fed into the models and the performance of each model was scrutinized based on three performance criteria.
doi:10.1080/1573062x.2018.1455880
fatcat:5mzcjbgqdzg2jpp7qvshgvqq5e