Genetic Programming to Predict Spillway Scour

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Omkar Deo and V. Jothiprakash and M. C. Deo",
  title =        "Genetic Programming to Predict Spillway Scour",
  journal =      "International Journal of Tomography \& Statistics",
  year =         "2008",
  volume =       "8",
  number =       "W08",
  pages =        "32--45",
  month =        "Winter",
  keywords =     "genetic algorithms, genetic programming, neural
                 networks, scour predictions spillway scour, skijump
  ISSN =         "0972-9976",
  URL =          "",
  size =         "14 pages",
  abstract =     "Investigators in the past had noticed that application
                 of a soft computing tool like artificial neural
                 networks (ANN) in place of traditional statistics based
                 data mining techniques produce more attractive results
                 in hydrologic as well as hydraulic predictions. Mostly
                 these works pertained to applications of ANN. Recently
                 another tool of soft computing namely genetic
                 programming (GP) has caught attention of researchers in
                 civil engineering computing. This paper examines the
                 usefulness of the GP based approach to predict the
                 depth and geometry of the scour hole produced
                 downstream of a common type of spillway, namely, the
                 ski-jump bucket. Hydraulic model measurements were used
                 to develop the GP models. The GP based estimations were
                 found to be equally, and possibly more, accurate than
                 the ANN based ones,especially when the underlying
                 cause-effect relationship became more uncertain to
  notes =        "Discipulus.

                 Datta Meghe College of Engineering, Airoli, Navi
                 Mumbai, 400708, India",

Genetic Programming entries for Omkar Deo V Jothiprakash M C Deo