Estimating PM2.5 concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, China

Estimating PM2.5 concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, China

With rapid economic growth, urbanization and industrialization, fine particulate matter with aerodynamic diameters ≤ 2.5 µm (PM2.5) has become a major pollutant and shows adverse effects on both human health and the atmospheric environment. Many studies on estimating PM2.5 concentrations have been p...

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Bibliographic Details
Main Authors: Ping Zhang, Wenjie Ma, Feng Wen, Lei Liu, Lianwei Yang, Jia Song, Ning Wang, Qi Liu
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Ecotoxicology and Environmental Safety
Subjects:
PM2.5
Machine learning
GA-SVM
Land use regression
Method improvement
Spatial clustering
Online Access:http://www.sciencedirect.com/science/article/pii/S0147651321008848

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