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On the predictability of short-lived particulate matter around a cement plant in Kerman, Iran: machine learning analysis
One of the greatest environmental risks in the cement industry is particulate matter emission (i.e., PM(2.5) and PM(10)). This paper aims to develop descriptive-analytical solutions for increasing the accuracy of predicting particulate matter emissions using resample data of Kerman cement plant. Pho...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643923/ https://www.ncbi.nlm.nih.gov/pubmed/36405244 http://dx.doi.org/10.1007/s13762-022-04645-3 |