Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique

  • Awatif Soaded Alsaqqar, Ass. Prof. Dr. College of Engineering-University of Baghdad
  • Basim Hussein Khudair, Ass. Prof. Dr. College of Engineering-University of Baghdad
  • Sura Kareem Ali, Dr College of Engineering-University of Baghdad
Keywords: artificial neural network; Reynar index; water stability; water treatment plants; correlation coefficient.

Abstract

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

 

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Published
2016-05-01
How to Cite
Alsaqqar, A., Khudair, B. and Ali, S. (2016) “Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique”, Journal of Engineering, 22(5), pp. 1-10. Available at: http://joe.uobaghdad.edu.iq/index.php/main/article/view/214 (Accessed: 19September2020).

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