Formation and identification of interrelations of causes and consequences of atmospheric air pollution in Almaty by methods of system analysis and artificial intelligence

Abstract

The problem of air pollution in Almaty is one of the topical issues today. In order to determine the opinion of experts and citizens of the city, a survey of the population of Almaty was conducted to assess the causes of air pollution in the city and the consequences that these pollutants entail. An expert assessment was carried out based on the data obtained from the survey for the causes and consequences of air pollution. Artificial intelligence algorithms with machine learning elements have been applied to build a model that determines the relationship between data on the causes of pollution and the consequences of atmospheric air pollution, and an analysis is carried out based on the results of the study. An algorithm for implementing the construction of the model is constructed. The results and metric estimates of the developed model are presented. The results of the study show that stationary, mobile sources and household and industrial waste have the greatest impact on public health and the environment.

This work is aimed at developing a unified ecosystem for collecting and processing air pollution monitoring data in industrial cities of Kazakhstan using modern monitoring systems, mathematical modeling and information and communication technologies.

Key words: atmospheric air pollution, system analysis, machine learning, expert assessment.