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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Detalles Bibliográficos
Autores principales: Wang, Deyun, Liu, Yanling, Luo, Hongyuan, Yue, Chenqiang, Cheng, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5551202/
https://www.ncbi.nlm.nih.gov/pubmed/28704955
http://dx.doi.org/10.3390/ijerph14070764

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