Capabilities offered by an adaptive neuro-fuzzy inference system (ANFIS) in the estimation of daily sediment loads at four stations in the USA, are explored in the paper. For this purpose, models with various input combinations of data sets were constructed to enable identification of the best possible structure. The results show that the best ANFIS model exhibits better performance compared to the SRC model, in terms of the RMSE, MBE and R2 values. The results also indicate that the ANFIS model can be applied to facilitate modelling of nonlinear dynamics of complex systems
The transport of sediment load in rivers is important with respect to pollution, channel navigabilit...
Abstract Accurate modeling and prediction of suspended sediment load (SSL) in rivers have an import...
This paper discusses the working mechanism of ANFIS, the flow of research, the implementation and ev...
Accurate forecasting of sediment is an important issue for reservoir design and water pollution cont...
Accurate forecasting of sediment is an important issue for reservoir design and water pollution cont...
The use of data-driven modelling (DDM) in hydrological forecasting has been in practice since decad...
This paper investigates the accuracy of an adaptive neuro-fuzzy computing technique in suspended sed...
Quantifying sediment load is vital for aquatic and riverine biota and has been the subject of variou...
Modeling of suspended sediment load in rivers has a major role in a proper management of water resou...
The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projec...
ANFIS (Adaptive Neuro Fuzzy Inference System), for its advantages of having linguistic representatio...
Abstract: This paper presented an investigation into the performance of system identification using ...
The interactions between fluid and sediment in the swash zone dominate the erosion or accretion of t...
Correct estimation of sediment volume carried by a river is very important for many water resources ...
Soft computing techniques are widely used for the applications on most of the nonlinear problems rel...
The transport of sediment load in rivers is important with respect to pollution, channel navigabilit...
Abstract Accurate modeling and prediction of suspended sediment load (SSL) in rivers have an import...
This paper discusses the working mechanism of ANFIS, the flow of research, the implementation and ev...
Accurate forecasting of sediment is an important issue for reservoir design and water pollution cont...
Accurate forecasting of sediment is an important issue for reservoir design and water pollution cont...
The use of data-driven modelling (DDM) in hydrological forecasting has been in practice since decad...
This paper investigates the accuracy of an adaptive neuro-fuzzy computing technique in suspended sed...
Quantifying sediment load is vital for aquatic and riverine biota and has been the subject of variou...
Modeling of suspended sediment load in rivers has a major role in a proper management of water resou...
The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projec...
ANFIS (Adaptive Neuro Fuzzy Inference System), for its advantages of having linguistic representatio...
Abstract: This paper presented an investigation into the performance of system identification using ...
The interactions between fluid and sediment in the swash zone dominate the erosion or accretion of t...
Correct estimation of sediment volume carried by a river is very important for many water resources ...
Soft computing techniques are widely used for the applications on most of the nonlinear problems rel...
The transport of sediment load in rivers is important with respect to pollution, channel navigabilit...
Abstract Accurate modeling and prediction of suspended sediment load (SSL) in rivers have an import...
This paper discusses the working mechanism of ANFIS, the flow of research, the implementation and ev...