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Modeling and Optimization of M-cresol Isopropylation for Obtaining N-thymol: Combining a Hybrid Artificial Neural Network with a Genetic Algorithm
1Institut National Polytechnique, Côte d’Ivoire, firstname.lastname@example.org
2Institut National Polytechnique, Côte d’Ivoire, email@example.com
3Institut National Polytechnique, Côte d’Ivoire
4Laboratoire de Génie Chimique, firstname.lastname@example.org
5Laboratoire de Génie Chimique, Andre.Davin@ensiacet.fr
Citation Information: International Journal of Chemical Reactor Engineering. Volume 5, Issue 1, Pages –, ISSN (Online) 1542-6580, DOI: 10.2202/1542-6580.1605, October 2007
- Published Online:
The application of a hybrid framework based on the combination, artificial neural network-genetic algorithm (ANN-GA), for n-thymol synthesis modeling and optimization has been developed. The effects of molar ratio propylene/cresol (X1), catalyst mass (X2) and temperature (X3) on n-thymol selectivity Y1 and m-cresol conversion Y2 were studied. A 3-8-2 ANN model was found to be very suitable for reaction modeling. The multiobjective optimization, led to optimal operating conditions (0.55 ? X1 ? 0.77; 1.773 g ? X2 ? 1.86 g; 289.74 °C ? X3 ? 291.33 °C) representing good solutions for obtaining high n-thymol selectivity and high m-cresol conversion. This optimal zone corresponded to n-thymol selectivity and m-cresol conversion ranging respectively in the interval [79.3; 79.5]% and [13.4 %; 23.7]%. These results were better than those obtained with a sequential method based on experimental design for which, optimum conditions led to n-thymol selectivity and m-cresol conversion values respectively equal to 67% and 11%. The hybrid method ANN-GA showed its ability to solve complex problems with a good fitting.