Genetic Programming to Predict Bridge Pier Scour

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "H. Md. Azamathulla and Aminuddin {Ab Ghani} and 
                 Nor Azazi Zakaria and Aytac Guven",
  title =        "Genetic Programming to Predict Bridge Pier Scour",
  journal =      "Journal of Hydraulic Engineering",
  year =         "2010",
  volume =       "136",
  number =       "3",
  pages =        "165--169",
  keywords =     "genetic algorithms, genetic programming, Local scour,
                 Bridge pier, Artificial neural networks, Radial basis
  DOI =          "doi:10.1061/(ASCE)HY.1943-7900.0000133",
  size =         "5 page",
  abstract =     "Bridge pier scouring is a significant problem for the
                 safety of bridges. Extensive laboratory and field
                 studies have been conducted examining the effect of
                 relevant variables. This note presents an alternative
                 to the conventional regression-based equations (HEC-18
                 and regression equation developed by authors), in the
                 form of artificial neural networks (ANNs) and genetic
                 programming (GP). 398 data sets of field measurements
                 were collected from published literature and used to
                 train the network or evolve the program. The developed
                 network and evolved programs were validated by using
                 the observations that were not involved in training.
                 The performance of GP was found more effective when
                 compared to regression equations and ANNs in predicting
                 the scour depth of bridge piers.",

Genetic Programming entries for Hazi Mohammad Azamathulla Aminuddin Ab Ghani Nor Azazi Zakaria Aytac Guven