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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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| Publicat a: | Int J Environ Res Public Health |
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| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2020
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| Matèries: | |
| Accés en línia: | 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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