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

Raja, Selvaraj and Thivaharan, Varadavenkatesan and Ramesh, Vinayagam and Ramachandra Murty, V (2014) Prediction of Viscosities of Aqueous Two Phase Systems Containing Protein by Artificial Neural Network. Journal of Chemical Engineering and Technology, 5 (3). pp. 3-5. ISSN 2157-7048

[img]
Preview
 PDF
2014 Publication - Dr S.RAJA.pdf - Published Version
Download (852kB) | Preview
Official URL: http://omicsonline.org/contact.php

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.

Item Type: Article
Uncontrolled Keywords: Aqueous two phase system; Artificial neural network; Levenberg-Marquardt (LM) algorithm; Grunberg-Nissan empirical mode
Subjects: Engineering > MIT Manipal > Biotechnology
Depositing User: MIT Library
Date Deposited: 20 May 2015 07:18
Last Modified: 20 May 2015 07:18
URI: http://eprints.manipal.edu/id/eprint/142696

Actions (login required)

View Item View Item