Journal of Dispersion Science and Technology, ( ISI ), Volume (34), No (4), Year (2013-4) , Pages (490-495)

Title : ( modeling of oil-water emulsion separation in ultrasound standing wave field by neural network )

Authors: Hanieh Ghafourian , Mohammad Taghi Hamed Mosavian , R. Kadkhodaee , Javad Sargolzaei ,

Citation: BibTeX | EndNote

A new approach has been introduced for separation of oil in water emulsion by using ultrasound standing wave field. Neural networks model was used to simulate changes in the size of droplet during treatment. Model outputs were then validated and it\\\\\\\'s generalization capability was evaluated. For each network, the optimum values of isotropic spread were obtained by minimizing the root mean square error and maximizing the corresponding coefficient. It was found that the predicted values were in good agreements with experimental results. Also, increasing voice speed was demonstrated to predict size of emulsion particles more efficiently and accurately.

Keywords

, Neural networks, o/w emulsion, RBF, separation,
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@article{paperid:1027865,
author = {Ghafourian, Hanieh and Hamed Mosavian, Mohammad Taghi and R. Kadkhodaee and Sargolzaei, Javad},
title = {modeling of oil-water emulsion separation in ultrasound standing wave field by neural network},
journal = {Journal of Dispersion Science and Technology},
year = {2013},
volume = {34},
number = {4},
month = {April},
issn = {0193-2691},
pages = {490--495},
numpages = {5},
keywords = {Neural networks; o/w emulsion; RBF; separation; ultrasound},
}

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%0 Journal Article
%T modeling of oil-water emulsion separation in ultrasound standing wave field by neural network
%A Ghafourian, Hanieh
%A Hamed Mosavian, Mohammad Taghi
%A R. Kadkhodaee
%A Sargolzaei, Javad
%J Journal of Dispersion Science and Technology
%@ 0193-2691
%D 2013

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