Application of genetic programming to develop the model for estimating membrane damage in the membrane integrity test using fluorescent nanoparticle

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Suh201180,
  author =       "Changwon Suh and Byeonggyu Choi and Seockheon Lee and 
                 Dooil Kim and Jinwoo Cho",
  title =        "Application of genetic programming to develop the
                 model for estimating membrane damage in the membrane
                 integrity test using fluorescent nanoparticle",
  journal =      "Desalination",
  volume =       "281",
  pages =        "80--87",
  year =         "2011",
  ISSN =         "0011-9164",
  DOI =          "doi:10.1016/j.desal.2011.07.045",
  URL =          "http://www.sciencedirect.com/science/article/pii/S001191641100659X",
  keywords =     "genetic algorithms, genetic programming, Membrane,
                 Integrity test, Fluorescent silica nanoparticle, Image
                 analysis",
  abstract =     "A new approach using silica fluorescent nanoparticle
                 as a surrogate for checking the integrity of
                 microfiltration membrane was proposed and well applied
                 in a previous study, but the absence of a feasible
                 estimation model for the degree of membrane damage
                 caused that this simple membrane integrity test was not
                 applied easily. This study proposes genetic programming
                 (GP) as an alternative approach to develop the model to
                 predict the area of membrane breach with other
                 experimental conditions (concentration of fluorescent
                 nanoparticle, the permeate water flux and transmembrane
                 pressure). Unlike the artificial neural network that is
                 the most common artificial intelligence technique, GP
                 is an inductive data-driven machine learning that
                 evolves an explicit equation with known experimental
                 data. The results obtained with GP models evolved were
                 satisfactory in predicting the area of the membrane
                 breach and, with the simple membrane integrity test,
                 the GP technique gives a practical way for estimating
                 the degree of membrane damage. Therefore, GP could
                 serve as a robust approach to develop an estimation
                 model for the new membrane integrity test.",
}

Genetic Programming entries for Chang-Won Suh Byeonggyu Choi Seockheon Lee Dooil Kim Jinwoo Cho

Citations