Prediction of PM<sub>2.5</sub> Concentration Using Spatiotemporal Data with Machine Learning Models

Prediction of PM<sub>2.5</sub> Concentration Using Spatiotemporal Data with Machine Learning Models

Among the critical global crises curbing world development and sustainability, air quality degradation has been a long-lasting and increasingly urgent one and it has been sufficiently proven to pose severe threats to human health and social welfare. A higher level of model prediction accuracy can pl...

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Bibliographic Details
Main Authors: Xin Ma, Tengfei Chen, Rubing Ge, Fan Xv, Caocao Cui, Junpeng Li
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Atmosphere
Subjects:
data mining
extremely randomized trees model
PM<sub>2.5</sub> prediction
random forest model
ridge regression model
support vector machine model
Online Access:https://www.mdpi.com/2073-4433/14/10/1517

Internet

https://www.mdpi.com/2073-4433/14/10/1517

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