Research Article Open Access

MODELING OF AMBIENT FOR SOx AND NOx POLLUTANTS THROUGH ARTIFICAL NEURAL NETWORK IN INDUSTRIAL AREA OF UJJAIN CITY

Abstract

The aim of this study was the modeling of ambient air pollutants through ANN in industrial area of Ujjain city in India and the study was carried out on modeling of air pollutants like SOx and NOx, using Artificial Neural Network. The ANN system was run by giving the inputs of meteriological datas and giving the outputs of concentration of various pollutants and accordingly the estimation of Errors was done by this study. The monthly datas in year from 2009 -2012 of meteorological like Temperature, Humidity, wind pressure and rainfall and the pollutants concentration were collected from the State Pollution Control Board. The ANN system used as shown in Figure 1 analyse all these datas and find the error coming during the experiment. The study estimated the Mean Square Error(MSE) from the inputs and outputs which were given to ANN in the industrial area of Ujjain City in India was found satisfactory as in the range of 0.001-0.003. The results shown here are indications that the neural network techniques can be useful tool in the hands of practitioners of air quality management and prediction. The models studied in this study are easily implemented, and they can deliver prediction in real time, unlike other modeling techniques.

PRIYANKA YADAV, ALKA SHRIVASTAVA, ASHOK .K.SHARMA AND J.K. SRIVASTAVA

To read the full article Download Full Article | Visit Full Article