• DocumentCode
    2315202
  • Title

    ANN Modeling for Prediction of Velocity in Channel Bends

  • Author

    Durge, P.V. ; Nagarnaik, P.B.

  • Author_Institution
    Civil Eng., B.N. Coll. of Eng., Pusad
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    1040
  • Lastpage
    1043
  • Abstract
    The flow in a channel bend is spiral or helical. It is a movement of water particles in the flow direction. Many researchers have stated mathematical equations to predict velocity in the flow direction in the channel bend. These equations are based on simplified assumptions. The ANN is a viable alternative to predict longitudinal velocity in channel bend. It builds the model by estimating suitable approximating function of the available input/output samples. Once such relationship is established & validated, it can be used for the prediction of the future system behavior. The paper aims at developing Artificial Neural Network model, namely Multilayer Perceptron (MLP). It is found that MLP model is capable to predict velocity in the channel bend with accuracy.
  • Keywords
    channel flow; multilayer perceptrons; physics computing; artificial neural network modeling; channel bend; flow direction; input-output sample function approximation; longitudinal velocity prediction; multilayer perceptron; water particle; Artificial neural networks; Educational institutions; Equations; Feedforward neural networks; Multilayer perceptrons; Neural networks; Predictive models; Propellers; Spirals; Velocity measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on
  • Conference_Location
    Nagpur, Maharashtra
  • Print_ISBN
    978-0-7695-3267-7
  • Electronic_ISBN
    978-0-7695-3267-7
  • Type

    conf

  • DOI
    10.1109/ICETET.2008.219
  • Filename
    4580056