Modeling the adsorption of phenols and nitrophenols by activated carbon using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Z-FLORES:2017:JCP,
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author = "Emigdio Z-Flores and Mohamed Abatal and Ali Bassam and
Leonardo Trujillo and Perla Juarez-Smith and
Youness {El Hamzaoui}",
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title = "Modeling the adsorption of phenols and nitrophenols by
activated carbon using genetic programming",
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journal = "Journal of Cleaner Production",
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volume = "161",
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pages = "860--870",
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year = "2017",
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keywords = "genetic algorithms, genetic programming, Water
treatment, Activated carbon, Phenols adsorption,
Regression",
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ISSN = "0959-6526",
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URL = "http://www.sciencedirect.com/science/article/pii/S0959652617311393",
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DOI = "doi:10.1016/j.jclepro.2017.05.192",
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abstract = "The process of adsorption of phenols and nitrophenols
by activated carbon is one of the most important types
of wastewater treatment. However, there is a lack of a
general analytic method to predict the adsorption
efficiency under different operating conditions. This
work studies a data driven approach towards modeling
the adsorption process, taking as input the type of
contaminant, the pH level, the initial concentration
and the elapsed time, in order to predict the
adsorption efficiency. In particular, this work is the
first to use genetic programming (GP), an evolutionary
computation paradigm for automatic program induction,
to address the stated modeling problem. Two recently
proposed GP algorithms are used and compared with other
regression techniques, using real-world experimental
data collected under typical operating conditions.
Results show that GP enhanced with a local search
operator (GP-LS) achieves the best results relative to
all other methods, achieving a median performance of
MSE=94.14, R2=0.92 and average solution size of 41
nodes. Therefore, this technique constitutes a
promising framework for the automatic modeling of the
adsorption efficiency",
- }
Genetic Programming entries for
Emigdio Z-Flores
Mohamed Abatal
Ali Bassam
Leonardo Trujillo
Perla Sarahi Juarez-Smith
Youness El Hamzaoui
Citations