Exploring PM2.5 and PM10 ML forecasting models: a comparative study in the UAE

Abstract Particulate Matters PM $$_{2.5}$$ and PM $$_{10}$$ present a major health and environmental concern in urban regions. This research compares machine learning and time series models, such as Decision Tree (DT), Random Forest (RF), Support Vector Regression (SVR), Convolutional Neural Network...

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Bibliografiske detaljer

Principais autores:	Waad Abuouelezz, Nazar Ali, Zeyar Aung, Ahmed Altunaiji, Shaik Basheeruddin Shah, Derek Gliddon
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2025-03-01
Serier:	Scientific Reports
Fag:	Machine learning Air pollution PM2.5 PM10 Decision tree Random forest
Online adgang:	https://doi.org/10.1038/s41598-025-94013-1
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