Prediction of Pollutant Removal in the Treatment Plant of Industrial Shahid Salimi Town Using ANN
Vahid Pakrou1 * , Saeed Pakrou1 , Naser Mehrdadi2 and Mohammad Javad Amiri2
1
Civil Engineering – Environmental,
Aras International Campus,
Iran
2
Civil Engineering – Environmental,
University of Tehran,
Iran
http://dx.doi.org/10.12944/CWE.10.Special-Issue1.109
Predicting the pollutant removal of the treatment plant of Shahid Salimi industrial town is performed in this study using artificial neural network. The required data of this treatment plant are achieved by 162 records after eliminating the repeated and uncompleted data. The appropriate inputs (BOD, COD, and TSS) are chosen by the correlation analysis in terms of having the highest correlation with the output parameters of the treatment plant, considering the small size of data sets and the need to simplify the model. The architecture of the network is used to make the proper prediction, which uses one neural network to predict all the output parameters (BOD, COD, and TSS). This network with 20 neurons in two hidden layers could predict the output of the treatment plant with good accuracy. Excellent results indicating the success of the modeling are obtained using the mentioned architecture.
Copy the following to cite this article:
Pakrou V, Pakrou S, Mehrdadi N, Amiri M. J. Prediction of Pollutant Removal in the Treatment Plant of Industrial Shahid Salimi Town Using ANN. Special Issue of Curr World Environ 2015;10(Special Issue May 2015). DOI:http://dx.doi.org/10.12944/CWE.10.Special-Issue1.109
Copy the following to cite this URL:
Pakrou V, Pakrou S, Mehrdadi N, Amiri M. J. Prediction of Pollutant Removal in the Treatment Plant of Industrial Shahid Salimi Town Using ANN. Special Issue of Curr World Environ 2015;10(Special Issue May 2015). Available from: http://cwejournal.org?p=697/
