Low visibility event prediction using random forest and K-nearest neighbor methods
Author:
Publisher
Springer Science and Business Media LLC
Subject
Atmospheric Science
Link
https://link.springer.com/content/pdf/10.1007/s00704-023-04697-6.pdf
Reference50 articles.
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2. Aldababseh A, Temimi M (2017) Analysis of the long-term variability of poor visibility events in the UAE and the link with climate dynamics. Atmosphere 8(12):242. https://doi.org/10.3390/atmos8120242
3. Alharbi B, Shareef MM, Husain T (2015) Study of chemical characteristics of particulate matter concentrations in Riyadh, Saudi Arabia. Atmos Pollut Res 6(1):88–98. https://doi.org/10.5094/APR.2015.011
4. Alhathloul SH, Khan AA, Mishra AK (2021) Trend analysis and change point detection of annual and seasonal horizontal visibility trends in Saudi Arabia. Theor Appl Climatol 144(1):127–146. https://doi.org/10.1007/s00704-021-03533-z
5. Ali N, Neagu D, Trundle P (2019) Evaluation of k-nearest neighbour classifier performance for heterogeneous data sets. SN App Sci 1(12):1559. https://doi.org/10.1007/s42452-019-1356-9
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