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Modelling of Urban Air Pollutant Concentrations with Artificial Neural Networks Using Novel Input Variables
Since operating urban air quality stations is not only time consuming but also costly, and because air pollutants can cause serious health problems, this paper presents the hourly prediction of ten air pollutant concentrations (CO(2), NH(3), NO, NO(2), NO(x), O(3), PM(1), PM(2.5), PM(10) and PN(10))...
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| Publicado no: | Int J Environ Res Public Health |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7143381/ https://ncbi.nlm.nih.gov/pubmed/32204378 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijerph17062025 |
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