Title : ( Neural network approach for modeling the mass transfer of potato slices during osmotic dehydration using genetic algorithm )
Authors: mohammad reza amiryousefi , Mohebbat Mohebbi ,
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Abstract
In this study, an approach for designing a neural network based on genetic algorithm has been used to model mass transfer during osmotic dehydration of potato slices. The experimental data were obtained through a complete randomized design with different osmotic solutions (5, 10 and 15% w/w) and potato to solution ratios (1:6, 1:8 and 1:10) at varying temperatures (30, 40 and 60°C) and the best model obtained with optimization of a multi-layer perceptron neural network had a mean absolute error of 0.260, 0.516 and 0.137 for moisture content, water loss and solid gain of osmotically dehydrated slices respectively.
Keywords
, Osmotic dehydration, potato, neural network, genetic algorithm, modeling, mass transfer
@article{paperid:1015284,
author = {Amiryousefi, Mohammad Reza and Mohebbi, Mohebbat},
title = {Neural network approach for modeling the mass transfer of potato slices during osmotic dehydration using genetic algorithm},
journal = {African Journal of Agricultural Research},
year = {2010},
volume = {5},
number = {1},
month = {January},
issn = {1991-637X},
pages = {70--77},
numpages = {7},
keywords = {Osmotic dehydration; potato; neural network; genetic algorithm; modeling; mass transfer},
}
%0 Journal Article
%T Neural network approach for modeling the mass transfer of potato slices during osmotic dehydration using genetic algorithm
%A Amiryousefi, Mohammad Reza
%A Mohebbi, Mohebbat
%J African Journal of Agricultural Research
%@ 1991-637X
%D 2010
