Air Pollutant Concentration Forecasting Using Long Short-Term Memory Based on Wavelet Transform and Information Gain: A Case Study of Beijing

Air pollutant concentration forecasting is an effective way which protects health of the public by the warning of the harmful air contaminants. In this study, a hybrid prediction model has been established by using information gain, wavelet decomposition transform technique, and LSTM neural network,...

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Detalles Bibliográficos
Autores principales: Liu, Bingchun, Guo, Xiaoling, Lai, Mingzhao, Wang, Qingshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545461/
https://www.ncbi.nlm.nih.gov/pubmed/33061948
http://dx.doi.org/10.1155/2020/8834699

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545461/
https://www.ncbi.nlm.nih.gov/pubmed/33061948
http://dx.doi.org/10.1155/2020/8834699

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