%0 Journal Article
%T 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
%A S. K. Lahiri
%A K. C. Ghanta
%J Chemical Industry and Chemical Engineering Quarterly
%D 2009
%I Association of the Chemical Engineers
%X 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.
%K artificial neural network
%K differential evolution
%K slurry hold up
%K slurry flow
%U http://www.ache.org.rs/CICEQ/2009/No2/CICEQ_Vol15_%20No2_pp103-117_Apr-Jun_2009.pdf