Genetic programming approach to predict a model acidolysis system
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- @Article{Ciftci:2009:EAEI,
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author = "Ozan Nazim Ciftci and Sibel Fadiloglu and
Fahrettin Gogus and Aytac Guven",
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title = "Genetic programming approach to predict a model
acidolysis system",
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journal = "Engineering Applications of Artificial Intelligence",
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year = "2009",
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volume = "22",
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pages = "759--766",
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number = "4-5",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, Acidolysis",
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DOI = "doi:10.1016/j.engappai.2009.01.010",
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ISSN = "0952-1976",
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URL = "http://www.sciencedirect.com/science/article/B6V2M-4VTVJNC-2/2/5894a9c11ade2e94a1ff09a18b63a062",
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abstract = "This paper models acidolysis of triolein and palmitic
acid under the catalysis of immobilized sn-1,3 specific
lipase. A gene-expression programming (GEP), which is
an extension to genetic programming (GP)-based model
was developed for the prediction of the concentration
of major reaction products of this reaction
(1-palmitoyl-2,3-oleoyl-glycerol (POO),
1,3-dipalmitoyl-2-oleoyl-glycerol (POP) and triolein
(OOO). Substrate ratio (SR), reaction temperature (T)
and reaction time (t) were used as input parameters.
The predicted models were able to predict the progress
of the reactions with a mean standard error (MSE) of
less than 1.0 and R of 0.978. Explicit formulation of
proposed GEP models was also presented. Considerable
good performance was achieved in modeling acidolysis
reaction by using GEP. The predictions of proposed GEP
models were compared to those of neural network (NN)
modeling, and strictly good agreement was observed
between the two predictions. Statistics and scatter
plots indicate that the new GEP formulations can be an
alternative to experimental models.",
- }
Genetic Programming entries for
Ozan Nazim Ciftci
Sibel Fadiloglu
Fahrettin Gogus
Aytac Guven
Citations