Application of Fuzzy Pattern Recognition Optimisation Model for Air Quality Assessment

A. K. Gorai
Air pollution monitoring program aims to monitor pollutants concentrations and its possible adverse effects at various locations over concerned area on the basis of air quality. Traditional air quality assessment is realized using air quality indices which are determined as mean values of selected air pollutants. Thus, air quality assessment depends on strictly prescribed limits without taking into account specific local conditions (like time of exposure and sensitivity of the people) and synergic relations between air pollutants. The stated limitations can be eliminated using fuzzy logic systems. Therefore, the paper presents a design of a model for air quality assessment based on fuzzy pattern recognition. This paper discusses the use of fuzzy pattern recognition technique in air quality risk assessment for a number of artificial dataset prepared for the present study. To demonstrate the application, common air pollutants like PM10, PM2.5, SO2, NOx, CO, and O3 are used as air pollutant parameters. Different air pollutants have varying in health impact and hence in air quality, the weightage of each pollutant are different. Thus, the weightage of air pollutant parameter are determined using analytical hierarchical process (AHP).
Air Quality Assessment; Fuzzy Pattern Recognition; Optimisation
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