A new predictive model for compressive strength of HPC using gene expression programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Seyyed Mohammad Mousavi and Pejman Aminian and 
                 Amir Hossein Gandomi and Amir Hossein Alavi and 
                 Hamed Bolandi",
  title =        "A new predictive model for compressive strength of HPC
                 using gene expression programming",
  journal =      "Advances in Engineering Software",
  year =         "2012",
  volume =       "45",
  number =       "1",
  pages =        "105--114",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, compressive strength,
                 regression analysis, sensitivity analysis, prediction,
                 high performance concrete",
  ISSN =         "0965-9978",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0965997811002535",
  DOI =          "doi:10.1016/j.advengsoft.2011.09.014",
  abstract =     "In this study, gene expression programming (GEP) is
                 used to derive a new model for the prediction of
                 compressive strength of high performance concrete (HPC)
                 mixes. The model is developed using a comprehensive
                 database obtained from the literature. The validity of
                 the proposed model is verified by applying it to
                 estimate the compressive strength of a portion of test
                 results that are not included in the analysis. Linear
                 and nonlinear least squares regression analyses are
                 performed to benchmark the GEP model. Contributions of
                 the parameters affecting the compressive strength are
                 evaluated through a sensitivity analysis. GEP is found
                 to be an effective method for evaluating the
                 compressive strength of HPC mixes. The prediction
                 performance of the optimal GEP model is better than the
                 regression models.",
  bibdate =      "2011-12-31",
  bibsource =    "DBLP,

Genetic Programming entries for Seyyed Mohammad Mousavi Pejman Aminian A H Gandomi A H Alavi Hamed Bolandi