A Neural Network Model for Prediction of Tri-Halo-Methane Concentration in Drinking Water

Subject Areas : environmental management

Mohammad Javad  Zoqi ¹ (Senior Expert of Environmental Engineering, Member of research institute of Environment of Jahad Daneshgahi)
Mohammad Ali  Jafari ² (Senior Expert of Environmental Engineering, Research institute of Environment of Jahad Daneshgahi)

Received: 2009-04-04 Accepted : 2009-06-07 Published : 2014-09-23

Keywords: Neural Network, tri-halo-methane concentration, chlorine, water quality parameters,

Abstract :

In this study a neural network model is proposed for modeling tri-halo-methane concentration indrinking water. After training, the neural network model predicts tri-halo-methane concentration basedon input data. Parameters such as pH, Temperature, free chlorine residue and TOC were used as inputdata. To validate the proposed method, a case study was carried out, based on the data obtained fromGuilan grand treatment plant (Sangar). The Levenberg-Marquardt algorithm was selected as the bestof thirteen back-propagation algorithms. The optimal neuron number for Levenberg-Marquardtalgorithm is 8 neurons. The performance of modeling was determined. The trends of the forecast andmeasured data were in good agreement.

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