Improving semi-empirical equations of ultimate bearing capacity of shallow foundations using soft computing polynomials

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@Article{Pan:2013:EAAI,
  author =       "Chan-Ping Pan and Hsing-Chih Tsai and Yong-Huang Lin",
  title =        "Improving semi-empirical equations of ultimate bearing
                 capacity of shallow foundations using soft computing
                 polynomials",
  journal =      "Engineering Applications of Artificial Intelligence",
  volume =       "26",
  number =       "1",
  pages =        "478--487",
  year =         "2013",
  keywords =     "genetic algorithms, genetic programming, Ultimate
                 bearing capacity, Shallow foundations, Semi-empirical
                 equations",
  ISSN =         "0952-1976",
  DOI =          "doi:10.1016/j.engappai.2012.08.014",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0952197612002151",
  abstract =     "This study presents the ultimate bearing capacity of
                 shallow foundations in meaningful ways and improves its
                 semi-empirical equations accordingly. Approaches
                 including weighted genetic programming (WGP) and soft
                 computing polynomials (SCP) are used to provide
                 accurate prediction and visible formulae/polynomials
                 for the ultimate bearing capacity. Visible formulas
                 facilitate parameter studies, sensitivity analysis, and
                 applications of pruning techniques. Analytical results
                 demonstrate that the proposed SCP is outstanding in
                 both prediction accuracy and provides simple
                 polynomials as well. Notably, the SCP identifies that
                 the shearing resistance angle and foundation geometry
                 impact on improving the Vesic's semi-empirical
                 equations.",
}

Genetic Programming entries for Chan-Ping Pan Hsing-Chih Tsai Yong-Huang Lin

Citations