Optimization of existing equations using a new Genetic Programming algorithm: Application to the shear strength of reinforced concrete beams

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

@Article{Perez201282,
  author =       "Juan L. Perez and Antoni Cladera and 
                 Juan R. Rabunal and Fernando Martinez-Abella",
  title =        "Optimization of existing equations using a new Genetic
                 Programming algorithm: Application to the shear
                 strength of reinforced concrete beams",
  journal =      "Advances in Engineering Software",
  volume =       "50",
  pages =        "82--96",
  year =         "2012",
  note =         "CIVIL-COMP",
  ISSN =         "0965-9978",
  DOI =          "doi:10.1016/j.advengsoft.2012.02.008",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0965997812000397",
  keywords =     "genetic algorithms, genetic programming, Artificial
                 intelligence, Structural engineering, Concrete, Shear
                 strength, Regression analysis",
  abstract =     "A method based on Genetic Programming (GP) to improve
                 previously known empirical equations is presented. From
                 a set of experimental data, the GP may improve the
                 adjustment of such formulae through the symbolic
                 regression technique. Through a set of restrictions,
                 and the indication of the terms of the expression to be
                 improved, GP creates new individuals. The methodology
                 allows us to study the need of including new variables
                 in the expression. The proposed method is applied to
                 the shear strength of concrete beams. The results show
                 a marked improvement using this methodology in relation
                 to the classic GP and international code procedures.",
}

Genetic Programming entries for Juan Luis Perez Antoni Cladera Bohigas Juan Ramon Rabunal Dopico Fernando Martinez Abella

Citations