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:1.8010
- @Article{Suh201180,
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author = "Changwon Suh and Byeonggyu Choi and Seockheon Lee and
Dooil Kim and Jinwoo Cho",
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title = "Application of genetic programming to develop the
model for estimating membrane damage in the membrane
integrity test using fluorescent nanoparticle",
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journal = "Desalination",
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volume = "281",
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pages = "80--87",
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year = "2011",
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ISSN = "0011-9164",
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DOI = "doi:10.1016/j.desal.2011.07.045",
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URL = "http://www.sciencedirect.com/science/article/pii/S001191641100659X",
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keywords = "genetic algorithms, genetic programming, Membrane,
Integrity test, Fluorescent silica nanoparticle, Image
analysis",
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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