The Air Quality Prediction Using HYBRID Soft Computing Techniques

Abstract

The common feature of many developing countries like INDIA is the deficiency of Environmental data. In INDIA, air quality is beginning to be systematically monitored in some places of the country. To overcome these problems, the need for accurate estimates of air quality levels becomes ever more important. To achieve such prediction tasks, the use of hybrid soft computing technique is regarded as a cost effective technique superior to traditional statistical methods. In this paper, neuro-fuzzy modelling for air quality prediction is used to estimate the well known pollutant i.e. Respiratory Suspended Particulate Matter (RSPM), from readily observable local meteorological data. The results indicate that the neuro-fuzzy model predicted air pollutant concentration with good accuracy of approximately 98%.

Keywords: Air quality, Artificial Neural Network, Hybrid Soft Computing Technique, neuro-fuzzy modelling.