MONIKA SINGH, S.P. MAHAPATRA AND S. NIGAM
Abstract
India, a developing economy is standing in front of a treacherous crisis of air pollution. Today, time of modernization relocation of peoples, transportation, industrial discharge, pollutant dispersions and dilution in a particular area is main causes of air pollution in a city. Chemical modification of pollutants in the atmosphere depends on the climatic and trophological parameters of that particular area. Delhi, one of the pollutants city of the world due to different causes and sources of pollutants is suffering from raise in concentration of pollutants present in air and making air unsafe for pleasant living. CO the main pollutant present in air causes many health and environmental issues. The breakpoint concentration of CO helps us to know the minimum concentration of pollutant in environment. This paper presents an artificial neural network based system for the efficient prediction of the CO concentration one day ahead. The proposed system has been trained with the previous one year CO data with five different inputs. It is reported that the short term prediction efficiency of the developed system is very high with very less prediction error of about 0.1095%.