Unveiling air pollution patterns in Yemen: a spatial–temporal functional data analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-023-25790-3.pdf
Reference84 articles.
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2. Acal C, Aguilera AM, Sarra A et al (2022) Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic. Stoch Environ Res Risk Assess 36:1083–1101. https://doi.org/10.1007/s00477-021-02071-4
3. Ahmad M, Rappenglück B, Osibanjo OO, Retama A (2022) A machine learning approach to investigate the build-up of surface ozone in Mexico-City. J Clean Prod 379:134638. https://doi.org/10.1016/j.jclepro.2022.134638
4. Al-Janabi S, Alkaim A (2022) A novel optimization algorithm (Lion-AYAD) to find optimal DNA protein synthesis. Egypt Informatics J 23:271–290. https://doi.org/10.1016/j.eij.2022.01.004
5. Al-Janabi S, Alkaim A, Al-Janabi E et al (2021) Intelligent forecaster of concentrations (PM2.5, PM10, NO2, CO, O3, SO2) caused air pollution (IFCsAP). Neural Comput Applic 33:14199–14229. https://doi.org/10.1007/s00521-021-06067-7
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