Prediction of Gas Pollutants Concentration by Means of Artificial Neural Network in Tehran Urban Air

Subject Areas : environmental management

Siamak  Bodaghpour ¹ ()
Amir  Charkhestani ² ()

Received: 2008-04-08 Accepted : 2008-07-22 Published : 2011-03-21

Keywords: Air pollution, Nitrogen Oxides, Carbonic Oxides, Nueral Net work, Time series,

Abstract :

In this study we applied artificial neural network (ANN) to predict the concentration of air pollutant in Tehran urban air. Because of dangers of air pollution in Tehran city witch causes environmental problems and various respiratory and dermatological diseases and troubles especially in children and aged people. This research was set in order to schedule and control this problem in Tehran and other great cities. Statistical data for this purpose were picked up from the concentration of pollutant gases recorded by fixed sensors in Bazar station from 2002 till 2007 (NOX gas). Auto regressive model and time series were used to determine neural network inputs. Current time gas concentration in this model depends on gas concentration of all 7 past days. Therefore, neural network input was concentration of the gas in all 7 past days and neural network output which was the prediction of neural network and the concentration of the gas in current time. Then the model of ANN is deigned by using of MATLAB 7 software and data simulating. Eventually, simulated data has plotted versus real data and it depicted that there is a good result compared with simulated data from ANN. The latter shows less error compare with regression model