Journal of Chemical Engineering & Process Technology
Open Access

Hachemaoui A

Publications

• Research Article
  An Artificial Neural Network Approach for the Prediction of Extraction Performance of Emulsion Liquid Membrane
  Author(s): Hachemaoui A and Belhamel KHachemaoui A and Belhamel K
  
  This paper reports the use of artificial neural networks (ANN) approach to predict nickel concentration in external phase during emulsion liquid membrane extraction process. Experimental data from laboratory batch analysis of nickel extraction have been used to train, validate and test the back-propagation ANN model. The input neurons correspond to, external phase pH, stripping phase concentration, stirring speed, carrier concentration, surfactant concentration, treatment ratio (volume ratio of emulsion to external phase), phase ratio (volume ratio of membrane to stripping phase), initial external phase nickel(II) concentration, and time. A tree -layer network with different hidden neurons and different learning algorithms such as LM, SCG, and BR were examined. The network with six hidden neurons and Bayesian regularization (BR) algorithm showed good performance. The predicted values of .. View More»
  DOI: 10.4172/2157-7048.1000356

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