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Day-Ahead PM(2.5) Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution
Accurate PM(2.5) concentration forecasting is crucial for protecting public health and atmospheric environment. However, the intermittent and unstable nature of PM(2.5) concentration series makes its forecasting become a very difficult task. In order to improve the forecast accuracy of PM(2.5) conce...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5551202/ https://www.ncbi.nlm.nih.gov/pubmed/28704955 http://dx.doi.org/10.3390/ijerph14070764 |