Assessment of relationship between PM10, PM2.5 and visibility in separation of synoptic codes, using Genetic Algorithm in Yazd

PM2.5, (PM10) and visibility are known as three important parameters in researches connected to the tropospheric aerosols and dusts, so that the air pollution is related to those at the specific time. The aim of this study is analyzing the relationship between PM2.5, PM10 and visibility whit using evolutional Genetic Algorithm. The area’s case study was Yazd city as representative of central of Iran. PM2.5s data and also visibilities data whit separation of 05, 06, 07 and 09 synoptic conditions, for 5 years (2010-2015) from Yazd Meteorology Organization; and PM10 data from air pollution control stations connected to Yazd Environment Organization has been catches. To reach mentioned mathematic relations, liner regression equation, and Weibull, Rational, Power, Polynomial, Exponential, Liner, Fourier and Gaussian functions has been comparison; which based on relative and Sum Square Error and also coefficient correlation, Polynomial function selects as the best fitness function. The results of this research were four equation based on liner model of Polynomial function in 95% confidence level, for estimating the relations between PM2.5, PM10 and visibility in general; and also when to happen 05, 06 and 07 synoptic conditions.