Genetic programming approach for prediction of compressive strength of concretes containing rice husk ash

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@Article{Saridemir20101911,
  author =       "Mustafa Saridemir",
  title =        "Genetic programming approach for prediction of
                 compressive strength of concretes containing rice husk
                 ash",
  journal =      "Construction and Building Materials",
  volume =       "24",
  number =       "10",
  pages =        "1911--1919",
  year =         "2010",
  ISSN =         "0950-0618",
  DOI =          "doi:10.1016/j.conbuildmat.2010.04.011",
  URL =          "http://www.sciencedirect.com/science/article/B6V2G-4YYVCMG-2/2/a49c4d90a50e50ba20756c5f87472767",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, Rice husk ash, Compressive
                 strength, Gene expression programming",
  abstract =     "Soft computing techniques have recently been widely
                 used to model some of human activities in many areas of
                 civil engineering applications. In this paper, two
                 models in gene expression programming (GEP) approach
                 for predicting compressive strength of concretes
                 containing rice husk ash have been developed at the age
                 of 1, 3, 7, 14, 28, 56 and 90 days. For purpose of
                 building the models, experimental results for 188
                 specimens produced with 41 different mixture
                 proportions are obtained from the literature. According
                 to these experimental results, the models are arranged
                 by using seven different input variables in GEP
                 approach. In according to these input variables, the
                 compressive strength values from mechanical properties
                 of concretes containing rice husk ash are predicted in
                 GEP approach models. The results of training, testing
                 and validation sets of the models are compared with
                 experimental results. All of the results showed that
                 GEP is a strong technique for the prediction of
                 compressive strength values of concretes containing
                 rice husk ash.",
}

Genetic Programming entries for Mustafa Saridemir

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