Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
Reference52 articles.
1. Ahmad, M., Alam, K., Tariq, S., Anwar, S., Nasir, J., & Mansha, M. (2019). Estimating fine particulate concentration using a combined approach of linear regression and artificial neural network. Atmospheric Environment, 219, 117050.
2. Anguita, D., Ghelardoni, L., Ghio, A., Oneto, L., & Ridella, S. (2012). The ‘K’in K-fold cross validation. In 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) (pp. 441–446).
3. Arciszewska, C., & McClatchey, J. (2001). The importance of meteorological data for modelling air pollution using ADMS-Urban. Meteorological Applications: A journal of forecasting, practical applications, training techniques and modelling, 8(3), 345–350.
4. Atash, F. (2007). The deterioration of urban environments in developing countries: Mitigating the air pollution crisis in Tehran, Iran. Cities, 24(6), 399–409.
5. Bagheri, H. (2022). A Machine Learning-based Framework for High Resolution Mapping of PM2.5 in Tehran, Iran, Using MAIAC AOD Data. Advances in space Research. In press.
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