Empirical modeling of shear strength of steel fiber reinforced concrete beams by gene expression programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{journals/nca/Kara13,
  title =        "Empirical modeling of shear strength of steel fiber
                 reinforced concrete beams by gene expression
                 programming",
  author =       "Ilker Fatih Kara",
  journal =      "Neural Computing and Applications",
  year =         "2013",
  number =       "3-4",
  volume =       "23",
  pages =        "823--834",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, GEP",
  bibdate =      "2013-09-24",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/nca/nca23.html#Kara13",
  URL =          "http://dx.doi.org/10.1007/s00521-012-0999-x",
  size =         "12 pages",
  abstract =     "The addition of steel fibres into concrete improves
                 the pestering tensile strength of hardened concrete and
                 hence significantly enhances the shear strength of
                 reinforced concrete reinforced concrete beams. However,
                 developing an accurate model for predicting the shear
                 strength of steel fiber reinforced concrete (SFRC)
                 beams is a challenging task as there are several
                 parameters such as the concrete compressive strength,
                 shear span to depth ratio, reinforcement ratio and
                 fibre content that affect the ultimate shear resistance
                 of FRC beams. This paper investigates the feasibility
                 of using gene expression programming (GEP) to create an
                 empirical model for the ultimate shear strength of SFRC
                 beams without stirrups. The model produced by GEP is
                 constructed directly from a set of experimental results
                 available in the literature. The results of training,
                 testing and validation sets of the model are compared
                 with experimental results. All of the results show that
                 GEP model is fairly promising approach for the
                 prediction of shear strength of SFRC beams. The
                 performance of the GEP model is also compared with
                 different proposed formulas available in the
                 literature. It was found that the GEP model provides
                 the most accurate results in calculating the shear
                 strength of SFRC beams among existing shear strength
                 formulae. Parametric studies are also carried out to
                 evaluate the ability of the proposed GEP model to
                 quantitatively account for the effects of shear design
                 parameters on the shear strength of SFRC beams.",
}

Genetic Programming entries for Ilker Fatih Kara

Citations