DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Mechanical and Civil Engineering (IJAMCE)-IJAMCE |
 Journal Home Volume Issue |
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Issue |
Volume-3,Issue-5 ( Oct, 2016 ) | |||||||||
Paper Title |
Modeling of River Water Quality Parameters Using Artificial Neural Network – A Case Study | |||||||||
Author Name |
Ammar Salman Dawood, Haleem K. Hussain, Aymanalak Hassan | |||||||||
Affilition |
Department of Civil Engineering, College of Engineering, University of Basrah, Iraq | |||||||||
Pages |
51-55 | |||||||||
Abstract |
In river water quality management, it is very important to use an effective approach to characterize complex water quality processes. This work is referred to the employment of Neural Network models to predict the water quality parameters in the Shatt Al Arab River. In the analysis of the models, the most ordinarily used feed forward error back propagation neural network technique has been utilized. Monthly data sets on turbidity, total hardness, total dissolved solids, and electrical conductivity have been employed for the analysis. The monthly data of four parameters, for the time period 2007-2012 were assigned for this analysis. The results present the ability of the suitable ANN models to predict the water quality parameters. This supplies a very useful tool for estimating the water quality of the Shatt Al Arab River. Key words- Water quality, ANN, Prediction, Shatt Al Arab River. | |||||||||
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