A novel seasonal index–based machine learning approach for air pollution forecasting-Reference-Cited by-同舟云学术

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A novel seasonal index–based machine learning approach for air pollution forecasting

Published:2022-05-13 Issue:6 Volume:194 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Khan Adeel,Sharma Sumit,Chowdhury Kaushik Roy,Sharma Prateek

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s10661-022-10092-x.pdf

Reference44 articles.

1. Abdulrazzaq, L. R., Abdulkareem, M. N., Yazid, M. R. M., Borhan, M. N., & Mahdi, M. S. (2020). Traffic congestion: Shift from private car to public transportation. Civil Engineering Journal (Iran), 6(8), 1547–1554. https://doi.org/10.28991/cej-2020-03091566

2. Agarwal, S., Sharma, S., Suresh, R., Rahman, M. H., Vranckx, S., Maiheu, B., Blyth, L., Janssen, S., Gargava, P., Shukla, V. K., & Batra, S. (2020). Air quality forecasting using artificial neural networks with real time dynamic error correction in highly polluted regions. Science of the Total Environment, 735, 139454. https://doi.org/10.1016/j.scitotenv.2020.139454

3. Anfossi, D., Brusasca, G., & Tinarelli, G. (1990). Simulation of atmospheric diffusion in low windspeed meandering conditions by a Monte Carlo dispersion method. Nuovo Cimento, C, 13(6), 995–1006. http://inis.iaea.org/Search/search.aspx?orig_q=RN:23004766

4. Angelevska, B., Atanasova, V., & Andreevski, I. (2021). Urban air quality guidance based on measures categorization in road transport. Civil Engineering Journal (Iran), 7(2), 253–267. https://doi.org/10.28991/cej-2021-03091651

5. Arroyo, Á., Herrero, Á., Tricio, V., Corchado, E., & Woźniak, M. (2018) Neural models for imputation of missing ozone data in air-quality datasets. Complexity, 2018. https://doi.org/10.1155/2018/7238015

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