Sedimentation in sewer pipes has a negative impact on the performance of sewerage systems. However, due to the complex nature of sedimentation, determining the governing equations is difficult and the results of the available classic models for computing bedload transport rate often differ from each other. This paper focuses on the capability of a support vector machine (SVM) as a meta-model approach for predicting bedload transport in pipes. The method was applied for the deposition and limit of deposition states of sediment transport. Two different scenarios were proposed: in Scenario 1, the input combinations were prepared using only hydraulic characteristics, on the other hand, Scenario 2 was built using both hydraulic and sediment characteristics as model inputs of bedload transport. A comparison between the SVM and the employed classic approaches in predicting sediment transport indicated the supreme performance of the SVM, in which more accurate results were obtained. Also it was found that for estimation of bedload transport in pipes, Scenario 2 led to a more valid outcome than Scenario 1. Based on the sensitivity analysis, parameters Frm and d50/y in the limit of deposition state and Frm in the deposition state had the more dominant role in prediction of bedload discharge in pipes than other parameters.
Prediction of non-cohesive sediment transport in circular channels in deposition and limit of deposition states using SVM
Kiyoumars Roushangar, Roghayeh Ghasempour; Prediction of non-cohesive sediment transport in circular channels in deposition and limit of deposition states using SVM. Water Supply 1 March 2017; 17 (2): 537–551. doi: https://doi.org/10.2166/ws.2016.153
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