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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...
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| Publicado no: | Int J Environ Res Public Health |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5551202/ https://ncbi.nlm.nih.gov/pubmed/28704955 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijerph14070764 |
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