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

A novel approach for modeling and optimization of surfactant/polymer flooding based on Genetic... •GP was used to model RF and NPV as a function of several important variables.•10-fold cross validation were employed to check the models overfitting.•Simultaneous optimization was performed on both models using Design Expert software.•Importance of all variables on both RF and NPV were investigated. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

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

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Publisher
Elsevier
Copyright
Copyright © 2016 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2016.03.095
Publisher site
See Article on Publisher Site

Abstract

•GP was used to model RF and NPV as a function of several important variables.•10-fold cross validation were employed to check the models overfitting.•Simultaneous optimization was performed on both models using Design Expert software.•Importance of all variables on both RF and NPV were investigated.

Journal

FuelElsevier

Published: Sep 1, 2016

References

  • Surfactants and their applications
    Schramm, L.L.; Stasiuk, E.N.; Marangoni, D.G.
  • A compositional simulator for modeling surfactant enhanced aquifer remediation, 1 formulation
    Delshad, M.; Pope, G.A.; Sepehrnoori, K.
  • Response Surface Methodology (RSM) as a tool for optimization in analytical chemistry
    Bezerra, M.A.; Santelli, R.E.; Oliveira, E.P.; Villar, L.S.; Escaleira, L.A.
  • Cross-validation for selecting a model selection procedure
    Zhang, Y.; Yang, Y.J.

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