A new genetic programming model for predicting settlement of shallow foundations

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Mohammad Rezania and Akbar A. Javadia",
  title =        "A new genetic programming model for predicting
                 settlement of shallow foundations",
  journal =      "Canadian Geotechnical Journal",
  year =         "2007",
  volume =       "44",
  number =       "12",
  pages =        "1462--1473",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, geotechnical
                 models, foundation settlement, granular soils,
                 evolutionary computation",
  ISSN =         "0008-3674",
  DOI =          "doi:10.1139/T07-063",
  size =         "12 pages",
  abstract =     "In this paper, a new genetic programming (GP) approach
                 for predicting settlement of shallow foundations is
                 presented. The GP model is developed and verified using
                 a large database of standard penetration test (SPT)
                 based case histories that involve measured settlements
                 of shallow foundations. The results of the developed GP
                 model are compared with those of a number of commonly
                 used traditional methods and artificial neural network
                 (ANN) based models. It is shown that the GP model is
                 able to learn, with a very high accuracy, the complex
                 relationship between foundation settlement and its
                 contributing factors, and render this knowledge in the
                 form of a function. The attained function can be used
                 to generalise the learning and apply it to predict
                 settlement of foundations for new cases not used in the
                 development of the model. The advantages of the
                 proposed GP model over the conventional and ANN based
                 models are highlighted.",
  notes =        "'Comparison of the results shows that predictions made
                 by the proposed GP model provide significant
                 improvements over the traditional methods and also
                 outperform the ANN models.' p1471",

Genetic Programming entries for Mohammad Rezania Akbar A Javadia