Neural network prediction of bed material load transport

@article{Kumar2012NeuralNP,
  title={Neural network prediction of bed material load transport},
  author={Bimlesh Kumar},
  journal={Hydrological Sciences Journal},
  year={2012},
  volume={57},
  pages={956 - 966}
}
  • B. Kumar
  • Published 1 July 2012
  • Engineering
  • Hydrological Sciences Journal
Abstract Bed material load, which comprises bed load and suspended load, has been extensively studied in the past few decades and many equations have been developed, but they differ from each other in derivation and form. If a process can be related to various flow conditions on a general basis, a proper understanding of bed material load movement can be ascertained. As the process is extremely complex, obtaining a deterministic or analytical form of it is too difficult. Neural network… 
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References

SHOWING 1-10 OF 69 REFERENCES
Artificial neural networks for sheet sediment transport
Abstract Sheet sediment transport was modelled by artificial neural networks (ANNs). A three-layer feed-forward artificial neural network structure was constructed and a back-propagation algorithm
Artificial neural network for bedload estimation in alluvial rivers
A talented soft computational technique is applied to predict bedload sediment discharge in rivers. The feedforward–backpropagated (Levenberg– Marquardt algorithm) Artificial Neural Network (ANN)
Multiple linear regression model for total bed material load prediction
A new total bed material load equation that is applicable for rivers in Malaysia was developed using multiple linear regression analyses. A total of 346 hydraulic and sediment data were collected
Estimation of total sediment load concentration obtained by experimental study using artificial neural networks
Estimation of sediment concentration in rivers is very important for water resources projects planning and managements. The sediment concentration is generally determined from the direct measurement
Prediction of Sediment Load Concentration in Rivers using Artificial Neural Network Model
An artificial neural model is used to estimate the natural sediment discharge in rivers in terms of sediment concentration. This is achieved by training the network to extrapolate several natural
Wash load and bed-material load transport in the Yellow River
It has been the conventional assumption that wash load is supply limited and is only indirectly related to the hydraulics of a river. Hydraulic engineers also assumed that bed-material load
Prediction of total bed material discharge
A new and user-friendly formula for the computation of total bed material load in alluvial channels under equilibrium transport conditions has been developed based on the stream power concept and
The potential rate of bed-load transport
  • B. Gomez
  • Environmental Science
    Proceedings of the National Academy of Sciences
  • 2006
TLDR
There is an upper, particle-size-dependent limit to bed-load transport efficiency, confirmed by averages made in three rivers characterized by a high availability of sediment in relation to runoff, and comparable data that represent the high end of the range of transport rates observed during three sets of laboratory experiments.
Total Load Transport Formula for Flow in Alluvial Channels
A user-friendly total bed-material load transport formula for flow in alluvial channels under equilibrium transport conditions has been developed based on dimensional analysis. The main advantages of
Comparisons of Selected Bed‐Material Load Formulas
Comparisons are made of the overall accuracy as well as the accuracy within different ranges of sediment concentration, Froude number, and slope for seven bed‐material load formulas. Four formulas
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