Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{GonzalezTaboada:2016:CBM,
  author =       "Iris Gonzalez-Taboada and Belen Gonzalez-Fonteboa and 
                 Fernando Martinez-Abella and Juan Luis Perez-Ordonez",
  title =        "Prediction of the mechanical properties of structural
                 recycled concrete using multivariable regression and
                 genetic programming",
  journal =      "Construction and Building Materials",
  volume =       "106",
  pages =        "480--499",
  year =         "2016",
  ISSN =         "0950-0618",
  DOI =          "doi:10.1016/j.conbuildmat.2015.12.136",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0950061815308072",
  abstract =     "This study focuses on the prediction of some of the
                 most important properties of structural recycled
                 concrete (compressive strength, modulus of elasticity
                 and splitting tensile strength) taking into account,
                 not only the recycled percentage and the quality of the
                 recycled aggregates used, but also the production
                 method. For said purpose, a database has been developed
                 with 1831 mixes obtained from 81 papers. Firstly, in
                 this manner, these properties have been compared with
                 those of conventional concrete. Then, the need to adapt
                 the prediction code expressions (adjusted for
                 conventional concretes) was analysed to take into
                 account the use of recycled concrete, developing, if
                 finally necessary, the correction coefficients which
                 allow engineers to predict the recycled properties with
                 the same approximation degree as in conventional
                 concretes. These correction coefficients have been
                 adjusted using multivariable regression, and have been
                 analysed using different statistical indexes. Lastly,
                 specific expressions used to predict these properties
                 in structural recycled concretes have been optimized.
                 Two different tools have been used to develop these
                 expressions: multivariable regression and genetic
                 programming. The proposed expressions have been
                 analysed using statistical parameters which have been
                 compared with those obtained using the expressions
                 proposed by other authors. In this regard, and finally,
                 the best prediction expressions for the modulus of
                 elasticity and the splitting tensile strength of
                 structural recycled concretes have been proposed.",
  keywords =     "genetic algorithms, genetic programming, Structural
                 recycled concrete, Database, Mixing procedure,
                 Mechanical properties, Multivariable regression",
}

Genetic Programming entries for Iris Gonzalez-Taboada Belen Gonzalez-Fonteboa Fernando Martinez Abella Juan Luis Perez

Citations