COMPARISON ON ARTIFICIAL NEURAL NETWORK AND SEDIMENT RATING CURVE MODELS FOR SIMULATING OF SUSPENDED SEDIMENT LOAD;CASE STUDY SHAHROOD WATERSHED

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MOHAMADI S.

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Journal: Journal of Irrigation and Water Engineering Year:2017 | Volume:7 | Issue:27 Page(s): 32-46

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Title

COMPARISON ON ARTIFICIAL NEURAL NETWORK AND SEDIMENT RATING CURVE MODELS FOR SIMULATING OF SUSPENDED SEDIMENT LOAD;CASE STUDY SHAHROOD WATERSHED

Author(s)

MOHAMADI S. | Issue Writer Certificate

Keywords

MULTI-LAYER PERCEPTRONQ2

RADIAL BASE FUNCTIONQ2

SHAHROODQ1

NASH COEFFICIENTQ1

SEDIMENT RATING CURVEQ2

Abstract

This research was conducted to compare the efficiency of some simulation models including SEDIMENT RATING CURVEs and artificial neural networks for simulating the suspended sediment load amount. Optimized model basis of flow discharge in SHAHROOD watershed upon the hydrometric stations including Glinak, Baghkalaye, Loshan and Rajayi dasht was represented. In order to simulate the suspended sediment load we compared one linear rating curve and artificial neural network with MULTI-LAYER PERCEPTRON and RADIAL BASE FUNCTION models. Then performance evaluation these models was carried out by NASH and RMSE criteria. The results showed that artificial neural network with MULTI-LAYER PERCEPTRON method in comparison on SEDIMENT RATING CURVE model in all of these stations simulated better models. So that artificial neural network with sigmoid triggering function in Glinak and Rajayi dasht stations with RMSE as 1.033 and 0.825 ton/day and NASH as 0.84 and 0.839 and this model with tansigmoid triggering function in Baghkalaye and Loshan stations with RMSE as 0.799 and 0.883 ton/day and NASH as 0.772 and 0.895, respectively, have the better efficiency for simulating of suspended sediment load amount. Also comparison of two neural network models showed that MLP model is better than RBF model for simulating of suspended sediment load amount. The only benefit of RBF networks is less time needed for training.

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APA: Copy

MOHAMADI, S.. (2017). COMPARISON ON ARTIFICIAL NEURAL NETWORK AND SEDIMENT RATING CURVE MODELS FOR SIMULATING OF SUSPENDED SEDIMENT LOAD;CASE STUDY SHAHROOD WATERSHED. IRANIAN OF IRRIGATION & WATER ENGINEERING, 7(27), 32-46. SID. https://sid.ir/paper/247108/en

Vancouver: Copy

MOHAMADI S.. COMPARISON ON ARTIFICIAL NEURAL NETWORK AND SEDIMENT RATING CURVE MODELS FOR SIMULATING OF SUSPENDED SEDIMENT LOAD;CASE STUDY SHAHROOD WATERSHED. IRANIAN OF IRRIGATION & WATER ENGINEERING[Internet]. 2017;7(27):32-46. Available from: https://sid.ir/paper/247108/en

IEEE: Copy

S. MOHAMADI, “COMPARISON ON ARTIFICIAL NEURAL NETWORK AND SEDIMENT RATING CURVE MODELS FOR SIMULATING OF SUSPENDED SEDIMENT LOAD;CASE STUDY SHAHROOD WATERSHED,” IRANIAN OF IRRIGATION & WATER ENGINEERING, vol. 7, no. 27, pp. 32–46, 2017, [Online]. Available: https://sid.ir/paper/247108/en

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