A novel approach for modeling and optimization of surfactant/polymer flooding based on Genetic Programming evolutionary algorithm

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@Article{Bahrami:2016:Fuel,
  author =       "Peyman Bahrami and Pezhman Kazemi and 
                 Sedigheh Mahdavi and Hossein Ghobadi",
  title =        "A novel approach for modeling and optimization of
                 surfactant/polymer flooding based on Genetic
                 Programming evolutionary algorithm",
  journal =      "Fuel",
  volume =       "179",
  pages =        "289--298",
  year =         "2016",
  ISSN =         "0016-2361",
  DOI =          "doi:10.1016/j.fuel.2016.03.095",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0016236116301375",
  abstract =     "In this research, Genetic Programming (GP) as a novel
                 method for modelling the Recovery Factor (RF) and the
                 Net Present Value (NPV) in Surfactant-Polymer (SP)
                 flooding is presented. The GP modelling, has the
                 advantage that the created models did not require a
                 fundamental description of the physical processes. The
                 GP created mathematical functions for both outputs as a
                 function of important parameters which involves in the
                 SP flooding based on 202 different data. Moreover,
                 10-fold cross validation were employed to check the
                 models overfitting. The Normalized Root Mean Squared
                 Error (NRMSE) and the coefficient of determination (R2)
                 of 4.83percent, 0.963 for the RF model, and
                 5.68percent, 0.946 for NPV model represented the
                 accuracy of models. The importance and effect of
                 variables on models were investigated, and simultaneous
                 optimization was performed on both models to find the
                 best results in terms of higher RF and NPV. The highest
                 values of 55.03 and 7.3 Million US Dollars (MMUSD) for
                 RF and NPV were achieved as a result of this
                 optimization.",
  keywords =     "genetic algorithms, genetic programming, RSM,
                 Optimization, Polymer-surfactant flooding, 10-Fold
                 cross validation",
  notes =        "Young Researchers and Elite Club, Science and Research
                 Branch, Islamic Azad University, Tehran, Iran Faculty
                 of Pharmacy, Departments of Pharmaceutical Technology
                 and Biopharmaceutics, Jagiellonian University, Krakow,
                 Poland",
}

Genetic Programming entries for Peyman Bahrami Pezhman Kazemi Sedigheh Mahdavi Hossein Ghobadi

Citations