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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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