Prediction of cement strength using soft computing techniques

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Adil Baykasoglu and Turkay Dereli and Serkan Tanis",
  title =        "Prediction of cement strength using soft computing
  journal =      "Cement and Concrete Research",
  year =         "2004",
  volume =       "34",
  pages =        "2083--2090",
  number =       "11",
  abstract =     "we aim to propose prediction approaches for the 28-day
                 compressive strength of Portland composite cement (PCC)
                 by using soft computing techniques. Gene expression
                 programming (GEP) and neural networks (NNs) are the
                 soft computing techniques that are used for the
                 prediction of compressive cement strength (CCS). In
                 addition to these methods, stepwise regression analysis
                 is also used to have an idea about the predictive power
                 of the soft computing techniques in comparison to
                 classical statistical approach. The application of the
                 genetic programming (GP) technique GEP to the cement
                 strength prediction is shown for the first time in this
                 paper. The results obtained from the computational
                 tests have shown that GEP is a promising technique for
                 the prediction of cement strength.",
  owner =        "wlangdon",
  URL =          "",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming, Gene
                 expression programming, Modelling, Compressive
                 strength, Cement manufacture",
  DOI =          "doi:10.1016/j.cemconres.2004.03.028",
  notes =        "


Genetic Programming entries for Adil Baykasoglu Turkay Dereli Serkan Tanis