Heavy metals in submicronic particulate matter (PM(1)) from a Chinese metropolitan city predicted by machine learning models

The aim of this study was to establish a method for predicting heavy metal concentrations in PM(1) (aerosol particles with an aerodynamic diameter ≤ 1.0 μm) based on back propagation artificial neural network (BP-ANN) and support vector machine (SVM) methods. The annual average PM(1) concentration w...

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Detalles Bibliográficos
Autores principales: Li, Huiming, Dai, Qian’ying, Yang, Meng, Li, Fengying, Liu, Xuemei, Zhou, Mengfan, Qian, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340598/
https://www.ncbi.nlm.nih.gov/pubmed/32721685
http://dx.doi.org/10.1016/j.chemosphere.2020.127571

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340598/
https://www.ncbi.nlm.nih.gov/pubmed/32721685
http://dx.doi.org/10.1016/j.chemosphere.2020.127571

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