A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
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Title
A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
Authors
Keywords
Air pollution, Artificial neural networks, Deep neural networks, Relative frequency, Fuzzy logic, Support vector machine, Systematic literature review
Journal
Journal of Cleaner Production
Volume 322, Issue -, Pages 129072
Publisher
Elsevier BV
Online
2021-09-18
DOI
10.1016/j.jclepro.2021.129072
References
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- (2019) Frederico M. Bublitz et al. International Journal of Environmental Research and Public Health
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- From diagnosis to prognosis for forecasting air pollution using neural networks: Air pollution monitoring in Bilbao
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