DEVELOPMENT OF AN ALGORITHM FOR PREDICTING ATMOSPHERIC AIR POLLUTION USING THE EXAMPLE OF DATA OF THE CITY OF UST-KAMENOGORSK

Abstract

Atmospheric air pollution is one of the urgent problems of modern cities. This article discusses the development of an algorithm for predicting the level of air pollution using the example of data from the city of Ust-Kamenogorsk. The use of machine learning in environmental monitoring tasks makes it possible to identify dangerous trends in a timely manner and take measures to minimize harm. The paper describes the main stages of model development, data analysis, algorithm selection and evaluation of its accuracy.