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Research Paper | Environmental Science Studies | India | Volume 5 Issue 8, August 2016 | Rating: 6.8 / 10
Modeling of Ambient Air Pollutants through Artificial Neural Network in Residential Area of Ujjain City
Alka Srivastava | Ashok K. Sharma
Abstract: The quality of air has become a major priority for worldwide health. The rise of human illness, because of pollution, leads to the gathering of new strategies for the levels of integrated systems of environmental management. The present paper subscribes to this concern and proposes a model for concentration prediction of airborne pollutants SOx, NOx, RSPM and SPM from a risk area (Sensitive area) in Ujjain City. The model uses the ANN system which analyze all these datas and find the error coming during the experiment. Actually the ANN can simulate this phenomenon, and in the present paper, values of the pollutants concentration from will be provisioned. The present ANN uses for training a number of variables and a large number of data (measured values). For the development and validation of the model it is necessary to have an adequate and continuous monitoring system for data. Airborne pollutants concentrations were measured with different instruments between December 2013 and December 2015. The comparison between the results from real measured data from sensitive area and the result of coming values provided a small maximum absolute error of 0.55.
Keywords: Artificial Neural Network, Mean Square Error, Suspended Particulate Matter, Respirable Suspended Particulate Matter, Sum Square error
Edition: Volume 5 Issue 8, August 2016,
Pages: 999 - 1001