Journal of Marine Science and Technology

Journal of Marine Science and Technology

Prediction of suspended sediment distribution of Karoon River using artificial neural network

Document Type : Original Manuscript

Authors
hossein bahrami 1
samad emamgholi zadeh 2
1 Department of Marine Structures, Faculty of Engineering, Khorramshahr University of marine science and technology
2 Department of Soil and Water, Faculty of Agriculture, shahrood industrial University
10.22113/jmst.2016.41032
Abstract
Accurate estimation of sediment concentrations in hydraulic sediment transport from different viewpoint such as sediment discharge estimation of river, selection of hydraulic structures and etc. are important. With respect to importance of this issue in this study for prediction of sediment concentration of Karun river multi-layer perceptron artificial neural network (ANN / MLP) was used.For this purpose 125 field data including bottom concentration, flow velocity, nearest distance from the beach, and thetotal depth of flow and flow depth was used.Three statistical metrics namely mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2) were used to evaluate the performance of ANN model. The result shows that MLP model with one hidden layer, Sigmoid transfer function and 5 neurons have best structure in the modeling of sediment concentration of Kroon River. The R2 and RMSE value is equal to 0.953 and 63.37 mg/l in training stage and 0.752 and 203.02 mg/l in testing stage, respectively. Finally, the sensitive analysis also showed that the nearest distance from the beachand flow depth had the most and the least effect on the sediment concentration, respectively.
Keywords
Modeling
Sediment Concentration
Artificial Neural Network
Karoon river

Subjects

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  • Receive Date 03 May 2016
  • Revise Date 26 November 2016
  • Accept Date 20 December 2016
  • Publish Date 23 July 2018