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2014 (Vol. 7, Issue: 1)
Article Information:

A Tumor Growth Model with Unmolded Dynamics Based on an Online Feedback Neural Network Model

ArashPourhashemi, Sara Haghighatnia, Nafiseh Mollaei, Reihaneh Kardehi Moghaddam and Hamid-Reza Kobravi
Corresponding Author:  ArashPourhashemi 

Key words:  Back-propagation, multi-layer perceptron, online feedback neural network, system identification, tumor growth model, ,
Vol. 7 , (1): 169-173
Submitted Accepted Published
May 16, 2013 June 12, 2013 January 01, 2014
Abstract:

In this study, we identify tumor growth system by an online feedback neural network model based on back-propagation method. The modeling and identification of nonlinear dynamic systems is the process of developing and improving a mathematical representation of a system using experimental data. So, it is a problem of considerable importance through the use of measured experimental data in biomedical modeling. As is obvious, in biomedical researches it is really difficult and in some cases impossible to implement research on real patient or such a system which is not possible to empirical tests. To deal with, we need sometime a model close to real system in order to forecast dynamic systems so as to perform researches on models and design controller for control of system.
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  Cite this Reference:
ArashPourhashemi, Sara Haghighatnia, Nafiseh Mollaei, Reihaneh Kardehi Moghaddam and Hamid-Reza Kobravi , 2014. A Tumor Growth Model with Unmolded Dynamics Based on an Online Feedback Neural Network Model.  Research Journal of Applied Sciences, Engineering and Technology, 7(1): 169-173.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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