Multivariate optimization of Pb(II) removal for clinoptilolite-rich tuffs using genetic programming: A computational approach
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- @Article{MAYTZUC:2018:CILS,
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author = "O. {May Tzuc} and A. Bassam and M. Abatal and
Youness {El Hamzaoui} and A. Tapia",
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title = "Multivariate optimization of {Pb(II)} removal for
clinoptilolite-rich tuffs using genetic programming: A
computational approach",
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journal = "Chemometrics and Intelligent Laboratory Systems",
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volume = "177",
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pages = "151--162",
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year = "2018",
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keywords = "genetic algorithms, genetic programming, Sensitivity
analysis, Sorption process, Swarm particle
optimization, Zeolite materials",
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ISSN = "0169-7439",
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DOI = "doi:10.1016/j.chemolab.2018.02.010",
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URL = "http://www.sciencedirect.com/science/article/pii/S0169743917306044",
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abstract = "In this study, a genetic programming (GP) model was
developed to predict and optimize the Pb(II) removal
capacity for natural, sodium, and acid-modified
clinoptilolite-rich tuffs. Experimental process
evaluated the sorption behavior of lead in aqueous
solutions using unmodified and modified natural zeolite
considering: the contact time, pH value, lead initial
concentration, and sorbent dosage. The GP model was
trained and tested with the experimental measurements
and subsequently, compared with others multivariate
analysis methods using three statistical criteria
(coefficient of determination (R2), root mean square
error (RMSE), and mean absolute percentage error
(MAPE)). The results indicate that GP getting the
better performance achieving a fitness of R2a =a
98.0percent, RMSEa =a 5.06a timesa 10-2, and MAPEa =a
17.58percent. Sensitivity analysis (SA) showed that the
sorbent dosage was the most influential parameter with
a sensitivity index of 0.219, following by the pH
(0.059), and contact time (0.031). Based on GP model
and SA, a multivariate optimization was conducted to
compute the adequate conditions for a required sorption
efficiency (98percent). Optimize values were obtained
at 0.10a g of sorbent mass, pH 5.0, 300.0a mga L-1, and
5.1a min contact time for natural clinoptilolite-rich
tuffs; 0.65a g of sorbent mass, pH 5.0, 400.0a mga L-1,
and 3.6a min contact time for sodium modified
clinoptilolite-rich tuffs; and 0.65a g of sorbent mass,
pH 3.0, 400.0a mga L-1, and 71.6a min contact time for
acid modified clinoptilolite-rich tuffs. The
computational approach presented can perform an
assessment with errors less than 6percent, indicating
that it is a promising tool for the modeling and
optimization of the sorption onto zeolite materials
minimizing the time and operation cost. The proposed
methodology can be used to take appropriate actions in
the removing of this toxic heavy metal from the water.
Besides, it can be implemented in studies corresponding
to other sorption processes or similar",
- }
Genetic Programming entries for
Oscar de Jesus May Tzuc
Ali Bassam
Mohamed Abatal
Youness El Hamzaoui
A Tapia
Citations