Effective Parameters on Determining the Damages of Water and Waste Water Branches using Artificial Neural Networks in Arak, Iran
Journal Title: International Research Journal of Applied and Basic Sciences - Year 2013, Vol 6, Issue 8
Abstract
Artificial Neural networks (ANNs) are used in various branches of engineering. Having an eye on he published articles on the subject, we can express the fact that there are wide horizons for the vast progresses in the engineering field. This study tries to determine the effects of the effective parameters on the damages of water and waste water network using artificial neural networks. The research takes into account six important parameters which are more likely to affect the water and waste water network. These parameters are cross, distributing valve, pipe, stop valve, joints and counter. In order to model the artificial neural networks and examine the effects of the above-mentioned parameters on water and waste water network, forty-five models have been used. They were obtained from data provided by Water and Waste Water Organization. The results show that the increase of damages in above-mentioned parameters causes the increase of quantity of damages in the whole branches. Regarding the approximate ways of calculating the quantity of damages of branches in the whole system, artificial neural networks can provide the acceptable accuracy because the error of %17 in these networks will anticipate the damages of the whole system of water and waste water branches in a satisfactory way. The objective of this research is to minimize and optimize the whole damages of water and waste water branches.
Authors and Affiliations
Sharif Afrogheh*| Islamic Azad University, Arak Science and Research Branch, Arak, Iran. email: sharifafrougheh3@yahoo.com, Abolfazl Saidi Far| Islamic Azad University, Arak Branch, Arak, Iran., Emad Roghanian| Islamic Azad University, Arak Branch, Arak, Iran., Iman Raeisizadeh| Khajeh Nasir University, Tehran Iran.
Keywords
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