Cargando…
PM2.5 forecasting for an urban area based on deep learning and decomposition method
Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe air pollution. Excessive emission of particulate matter to ambient air has negatively impacted the health and well-being of human society. Therefore, ac...
Autores principales: | Zaini, Nur’atiah, Ean, Lee Woen, Ahmed, Ali Najah, Abdul Malek, Marlinda, Chow, Ming Fai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584903/ https://www.ncbi.nlm.nih.gov/pubmed/36266317 http://dx.doi.org/10.1038/s41598-022-21769-1 |
Ejemplares similares
-
Developing machine learning algorithms for meteorological temperature and humidity forecasting at Terengganu state in Malaysia
por: Hanoon, Marwah Sattar, et al.
Publicado: (2021) -
Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia
por: Che Wan Zanial, Wan Norsyuhada, et al.
Publicado: (2023) -
Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia
por: Adli Zakaria, Muhamad Nur, et al.
Publicado: (2023) -
Population Exposure to PM(2.5) in the Urban Area of Beijing
por: Zhang, An, et al.
Publicado: (2013) -
Research on a Novel Hybrid Decomposition–Ensemble Learning Paradigm Based on VMD and IWOA for PM(2.5) Forecasting
por: Guo, Hengliang, et al.
Publicado: (2021)