Combining forward with recurrent neural networks for hourly air quality prediction in Northwest of China-Reference-Cited by-同舟云学术

Combining forward with recurrent neural networks for hourly air quality prediction in Northwest of China

Published:2020-05-17 Issue:23 Volume:27 Page:28931-28948
ISSN:0944-1344
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Zhao Zhili,Qin Jian,He Zhaoshuang,Li Huan,Yang Yi,Zhang Ruisheng

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s11356-020-08948-1.pdf

Reference45 articles.

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3. AirVisual I (2018) 2018 world air quality report-region & city pm2.5 ranking, Tech. Rep.

4. Atabay D (2019) pyrenn: a recurrent neural network toolbox for python and matlab–pyrenn 0.1 documentation. https://pyrenn.readthedocs.io/en/latest/ . Accessed 02 Jul 2019

5. Athira V, Geetha P, Vinayakumar R, Soman KP (2018) Deepairnet: applying recurrent networks for air quality prediction. Procedia Computer Science 132:1394–1403. Retrieved from http://www.sciencedirect.com/science/article/pii/S1877050918308007 (International Conference on Computational Intelligence and Data Science)

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