Fuzzy modeling of atmospheric dustiness in Kyiv

Abstract

Based on the fuzzy logic model, the atmospheric air dustiness index in the city of Kyiv was calculated based on the results of measuring the concentration of solid particles such as PM1, PM2.5 and PM10 by environmental monitoring stations. The model has a 301-point scale, which at its borders is compatible with the AQI Air Quality Index determination scale from the Environmental Protection Agency (EPA) (USA). The model is built according to the Mamdani algorithm and has three inputs and one output with three membership functions each. The input data is the concentration values of solid particles such as PM1, PM2.5, and PM10. The fuzzy rule database has 27 fuzzy inference formulas. The model is developed in the MATLAB package and can be the basis of an expert system for assessing the level of danger to human health based on the results of measuring the concentration of solid particles, primarily fractions with low dispersion.

Keywords

• air quality index
• solid particles
• fuzzy logic
• mamdani algorithm
• fuzzy inference rules