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ISSN: 2157-7048

Journal of Chemical Engineering & Process Technology
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Research Article

Prediction of Viscosities of Aqueous Two Phase Systems Containing Protein by Artificial Neural Network

Selvaraj Raja*, Varadavenkatesan Thivaharan, Vinayagam Ramesh and Vytla Ramachandra Murty
Department of Biotechnology, Manipal Institute of Technology, Manipal, Karnataka, India
Corresponding Author : Selvaraj Raja
Department of Biotechnology
Manipal Institute of Technology
Manipal, Karnataka-576104, India
Tel: +9108202924322
Fax: +9108202571071
E-mail: [email protected]
Received March 21, 2014; Accepted April 26, 2014; Published April 30, 2014
Citation: Raja S, Thivaharan V, Ramesh V, Murty VR (2014) Prediction of Viscosities of Aqueous Two Phase Systems Containing Protein by Artificial Neural Network. J Chem Eng Process Technol 5:192. doi:10.4172/2157-7048.1000192
Copyright: © 2014 Raja S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author andsource are credited.
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Abstract

The viscosities of aqueous two phase system containing bovine serum albumin (BSA) were predicted by artificial neural network (ANN) as a function of concentration of poly-ethylene-glycol (PEG), concentration of BSA and temperature. A three layer feed forward neural network based on Levenberg-Marquardt (LM) algorithm which consisted of three input neurons, 10 hidden neurons and one output neuron (3:10:1) was developed. The performance parameters were calculated and compared with the conventional Grunberg-Nissan empirical model. The satisfactory values suggest that the proposed ANN model has the capability of predicting viscosity in a better way than the conventional empirical model.

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