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Air qualityassessment model Degtyareva KseniaTynchenko VadimKukartseva Svetlana2024 год

Air quality assessment model
статья из журнала

Дополнительные ссылки: eLibrary
База данных: Каталог библиотеки СФУ
Библиографическое описание: Air quality assessment model : научное издание / K. K. Degtyareva, V. V. Tynchenko, S. S. Kukartseva. - Текст : непосредственный // E3S Web of Conferences. - 2024. - Т. 583, № . - С. 02004. - ISSN 2555-0403. - ISSN 2267-1242, 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 factors 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>
Год издания: 2024
Авторы: Degtyareva Ksenia, Tynchenko Vadim, Kukartseva Svetlana
Издательство: EDP Sciences - Web of Conferences, Les Ulis
Источник: E3S Web of Conferences
Выпуск: Т. 583
Номера страниц: 02004
Количество экземпляров:
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