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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 4 | Page No.: 615-621
DOI: 10.3923/jas.2008.615.621
Prediction of Vapor-Liquid Equilibrium for Aqueous Solutions of Electrolytes Using Artificial Neural Networks
A. Ghaemi, Sh. Shahhoseini, M. Ghannadi Marageh and M. Farrokhi

Abstract:
In this study, an Artificial Neural Network (ANN) model has been developed for aqueous solutions of electrolyte systems. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) networks were applied to estimate vapor-liquid equilibrium data for ternary system of NH3-CO2-H2O. Experimental data, taken from the literature were divided into three sections of training, validating and testing. Mean Absolute Errors (MAE) of the networks for training set are used as network selection criterion and to find optimal design of the networks. The performance of ANN models to predict partial and total pressures of NH3-CO2-H2O system were evaluated by comparing their results with the predictions of some thermodynamic models. The criterion for this comparison was the error between models perditions and the experimental data. The comparison indicated that both MLP and RBF models predict the system better than the thermodynamic models.
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How to cite this article:

A. Ghaemi, Sh. Shahhoseini, M. Ghannadi Marageh and M. Farrokhi, 2008. Prediction of Vapor-Liquid Equilibrium for Aqueous Solutions of Electrolytes Using Artificial Neural Networks. Journal of Applied Sciences, 8: 615-621.

DOI: 10.3923/jas.2008.615.621

URL: https://scialert.net/abstract/?doi=jas.2008.615.621

 
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