comparison of daily suspended sediment load estimations by sediment rating curve and neural network models (case study: ghazaghli station in golestan province)
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Estimating Suspended Sediment by Artificial Neural Network (ANN), Decision Trees (DT) and Sediment Rating Curve (SRC) Models (Case study: Lorestan Province, Iran)
The aim of this study was to estimate suspended sediment by the ANN model, DT with CART algorithm and different types of SRC, in ten stations from the Lorestan Province of Iran. The results showed that the accuracy of ANN with Levenberg-Marquardt back propagation algorithm is more than the two other models, especially in high discharges. Comparison of different intervals in models showed that r...
متن کاملestimation suspended sediment load with sediment rating curve and artificial neural network method (case study: lorestan province)
suspended sediment estimation is an important factor from different aspects including, farming, soil conservation, dams, aquatic life, as well as various aspects of the research. there are different methods for suspended sediment estimation. this study aims to estimate suspended sediment using feed forward neural network with error back propagation with levenberg-marquardt back propagation algo...
متن کاملInvestigation of Possibility of Suspended Sediment Prediction Using a Combination of Sediment Rating Curve and Artificial Neural Network Case Study: Ghatorchai River, Yazdakan Bridge
Estimation of sediment loads in rivers is one of the most important, difficult components of sediment transport studies and river engineering. Accessing new methods that can be effective in this background are more important. In this research, we have used the artificial neural network (ANN) to optimize the results of the sediment rating curve (SRC) to predict the suspended sediment loads. For ...
متن کاملInvestigation of Temporal Phenomena of Sediment Rating Curve and comparison of it with the Some Statistical Methods for Estimating Suspended Sediment Load (Case study: Gamasiab Watershed)
The variable and complex nature of the sediment load of rivers has led that the estimation of sediment entering the reservoirs and the production of long term sediment, for determining the lifetime of the structures encounter with the problem. Application of sediment rating curves is one of the most common methods for estimating the suspended sediment load of rivers. Regardless of the accuracy ...
متن کاملestimating suspended sediment by artificial neural network (ann), decision trees (dt) and sediment rating curve (src) models (case study: lorestan province, iran)
the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...
متن کاملApplying Artificial Neural Network Algorithms to Estimate Suspended Sediment Load (Case Study: Kasilian Catchment, Iran)
Estimate of sediment load is required in a wide spectrum of water resources engineering problems. The nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods to simulate the suspended sediment load. In this study Artificial Neural Networks (ANNs) are employed to estimate daily suspended sediment load. Two different ANN algorithms, Multi Layer Perce...
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پژوهش های حفاظت آب و خاکجلد ۲۰، شماره ۲، صفحات ۲۲۱-۲۳۰
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