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IRAQI JOURNAL OF STATISTICAL SCIENCES

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A Comparison Between Support Vector Machine for Regression (SVR) and Neural Network Back- Propagation (BPNN) :Applied Study for Tigris Water Monthly Flow in Mosul City .

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2013, Volume 13, Issue 2, Pages 114-130
10.33899/iqjoss.2013.80688

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Abstract

Abstract :
The idea of this research is based on adopting Support Vector Machine for Regression (SVR) in estimating and predicting regression models and comparing it with one of the multi layer neural network that has back propagation((MLP). Therefore ,this will lead to demonstrate the advantages and possibility to use it in scientific application by illustrating how it is accurate in comparison with the ((MLP) by using Mean Square Errors(MSe) .
The time sequence data are that used for month flow for the water from Tigris that incomes in to Mosul city for the period between (1950-1995) to accomplish the comparison process by using the employment of two computers softwares.
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(2013). A Comparison Between Support Vector Machine for Regression (SVR) and Neural Network Back- Propagation (BPNN) :Applied Study for Tigris Water Monthly Flow in Mosul City .. IRAQI JOURNAL OF STATISTICAL SCIENCES, 13(2), 114-130. doi: 10.33899/iqjoss.2013.80688
. "A Comparison Between Support Vector Machine for Regression (SVR) and Neural Network Back- Propagation (BPNN) :Applied Study for Tigris Water Monthly Flow in Mosul City .". IRAQI JOURNAL OF STATISTICAL SCIENCES, 13, 2, 2013, 114-130. doi: 10.33899/iqjoss.2013.80688
(2013). 'A Comparison Between Support Vector Machine for Regression (SVR) and Neural Network Back- Propagation (BPNN) :Applied Study for Tigris Water Monthly Flow in Mosul City .', IRAQI JOURNAL OF STATISTICAL SCIENCES, 13(2), pp. 114-130. doi: 10.33899/iqjoss.2013.80688
A Comparison Between Support Vector Machine for Regression (SVR) and Neural Network Back- Propagation (BPNN) :Applied Study for Tigris Water Monthly Flow in Mosul City .. IRAQI JOURNAL OF STATISTICAL SCIENCES, 2013; 13(2): 114-130. doi: 10.33899/iqjoss.2013.80688
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