Тип публикации: статья из журнала
Год издания: 2024
Идентификатор DOI: 10.1051/e3sconf/202458302004
Аннотация: <jats:p>This study examines the application of machine learning methods to predict air quality in Brisbane, Australia. The main attention is paid to the creation of a model capable of predicting the concentration of PM10 suspended particles based on meteorological data. In the course of the work, a statistical analysis of the factoПоказать полностьюrs influencing the level of pollution was carried out, and a random forest model was developed and tested. The results showed that the model is able to explain about 69% of the variation in PM10 concentration, and also identified key meteorological parameters such as air temperature and wind speed that have the greatest impact on the concentration of pollutants. The data obtained can be used to improve the monitoring and management of air quality in cities, which in the future may contribute to reducing the harmful effects of pollution on public health.</jats:p>
Журнал: E3S Web of Conferences
Выпуск журнала: Т. 583
Номера страниц: 02004
ISSN журнала: 25550403
Место издания: Les Ulis
Издатель: EDP Sciences - Web of Conferences