Compressive strength of geopolymers produced by ordinary Portland cement: Application of genetic programming for design

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@Article{Nazari:2013:MD,
  author =       "Ali Nazari",
  title =        "Compressive strength of geopolymers produced by
                 ordinary Portland cement: Application of genetic
                 programming for design",
  journal =      "Material \& Design",
  volume =       "43",
  pages =        "356--366",
  year =         "2013",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, Geopolymer, Portland cement,
                 Compressive strength",
  ISSN =         "0261-3069",
  DOI =          "doi:10.1016/j.matdes.2012.07.012",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0261306912004645",
  abstract =     "In the present study, compressive strength results of
                 geopolymers produced by ordinary Portland cement (OPC)
                 as aluminosilicate source has been modelled by gene
                 expression programming. Six main factors including NaOH
                 concentration, water glass to NaOH weight ratio, alkali
                 activator to cement weight ratio, oven curing
                 temperature, oven curing time and water curing regime
                 each at four levels were considered for designing. A
                 total of 32 experiments were conducted according to the
                 L32 array proposed by the method. The gene expression
                 programming models were constructed by 10 input
                 parameters including NaOH concentration, water glass to
                 NaOH weight ratio, alkali activator to cement weight
                 ratio, oven curing Temperature, oven curing time, water
                 curing regime, water glass content, NaOH content,
                 Portland cement content and test trial number. The
                 value for the output layer was the compressive
                 strength. According to the input parameters in the
                 models, the constructed networks were trained and
                 tested. The results indicate that gene expression
                 programming model is a powerful tool for predicting the
                 compressive strength of the geopolymers in the
                 considered range.",
}

Genetic Programming entries for Ali Nazari

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