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Artificial neural network model with the parameter tuning assisted by a differential evolution technique: the study of the hold up of the slurry flow in a pipeline

Author(s): S. K. Lahiri | K. C. Ghanta

Journal: Chemical Industry and Chemical Engineering Quarterly
ISSN 1451-9372

Volume: 15;
Issue: 2;
Start page: 103;
Date: 2009;
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Keywords: artificial neural network | differential evolution | slurry hold up | slurry flow

This paper describes a robust hybrid artificial neural network (ANN) methodology which can offer a superior performance for the important process engineering problems. The method incorporates a hybrid artificial neural network and differential evolution technique (ANN-DE) for the efficient tuning of ANN meta parameters. The algorithm has been applied for the prediction of the hold up of the solid liquid slurry flow. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved the prediction of hold up over a wide range of operating conditions, physical properties, and pipe diameters.
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