A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach

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A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach

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作者：Scott Weichenthal^a ; ^d ; ^{scott.weichenthal@hc-sc.gc.ca" class="auth_mail" title="E-mail the corresponding author} ; Keith Van Ryswyk^a ; Alon Goldstein^b ; Scott Bagg^b ; Maryam Shekkarizfard^c ; Marianne Hatzopoulou^e
关键词：Ultrafine particles ; Land use regression ; Traffic ; Built environment
刊名：Environmental Research
出版年：2016
出版时间：April 2016
年：2016
卷：146
期：Complete
页码：65-72
全文大小：1035 K

文摘

•: We developed a land use regression model for ultrafine particles in Montreal, Canada.
•: Model development was based on data collected from 414 road segments.
•: Final models explained the majority of spatial variations in ambient ultrafine particles.
•: Final models performed well when evaluated using cross-validation or an external dataset.

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