High-Precision Modeling of Uplift Capacity of Suction Caissons Using a Hybrid Computational Method

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@Article{Alavi:2010:GeoMechEng,
  author =       "Amir Hossein Alavi and Amir Hossein Gandomi and 
                 Mehdi Mousavi and Ali Mollahasani",
  title =        "High-Precision Modeling of Uplift Capacity of Suction
                 Caissons Using a Hybrid Computational Method",
  journal =      "Geomechanics and Engineering",
  year =         "2010",
  volume =       "2",
  number =       "4",
  pages =        "253--280",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, suction
                 caissons, uplift capacity, simulated annealing,
                 nonlinear modelling",
  URL =          "http://technopress.kaist.ac.kr/?page=container&journal=gae&volume=2&num=4",
  DOI =          "doi:10.12989/gae.2010.2.4.253",
  abstract =     "A new prediction model is derived for the uplift
                 capacity of suction caissons using a hybrid method
                 coupling genetic programming (GP) and simulated
                 annealing (SA), called GP/SA. The predictor variables
                 included in the analysis are the aspect ratio of
                 caisson, shear strength of clayey soil, load point of
                 application, load inclination angle, soil permeability,
                 and loading rate. The proposed model is developed based
                 on well established and widely dispersed experimental
                 results gathered from the literature. To verify the
                 applicability of the proposed model, it is employed to
                 estimate the uplift capacity of parts of the test
                 results that are not included in the modelling process.
                 Traditional GP and multiple regression analyses are
                 performed to benchmark the derived model. The external
                 validation of the GP/SA and GP models was further
                 verified using several statistical criteria recommended
                 by researchers. Contributions of the parameters
                 affecting the uplift capacity are evaluated through a
                 sensitivity analysis. A subsequent parametric analysis
                 is carried out and the obtained trends are confirmed
                 with some previous studies. Based on the results, the
                 GP/SA-based solution is effectively capable of
                 estimating the horizontal, vertical and inclined uplift
                 capacity of suction caissons. Furthermore, the GP/SA
                 model provides a better prediction performance than the
                 GP, regression and different models found in the
                 literature. The proposed simplified formulation can
                 reliably be employed for the pre-design of suction
                 caissons. It may be also used as a quick check on
                 solutions developed by more time consuming and in-depth
                 deterministic analyses.",
}

Genetic Programming entries for A H Alavi A H Gandomi Mehdi Mousavi Ali Mollahasani

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