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dc.contributor.author |
Gherfi, Kaddour |
|
dc.date.accessioned |
2025-03-18T11:23:02Z |
|
dc.date.available |
2025-03-18T11:23:02Z |
|
dc.date.issued |
2024 |
|
dc.identifier.uri |
http://depot.umc.edu.dz/handle/123456789/14546 |
|
dc.description.abstract |
Weather prediction is a crucial tool for a wide range of applications, including
ag-riculture, transportation, and disaster preparedness and response. It remains
one of the most complex scientific and technological challenges worldwide. In
the current study, we investigate the effectiveness of one of the most accurate
and adopted machine learning algorithms in various fields, which is K-Nearest
Neighbors (KNN), the obtained results demonstrate that KNN is a promising
method for weather prediction, achiving an accuracy=85,07 on weatherHistory
dataset. |
fr_FR |
dc.title |
Machine learning weather prediction |
fr_FR |
dc.type |
Article |
fr_FR |
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