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Gjeka, Erestina
2025-07-07T11:05:29Z
2025-07-07T11:05:29Z
2024-10
2560-2810hu_HU
http://hdl.handle.net/20.500.14044/30328
Climate change has affected every sector of nature, especially healthcare in recent years. These changes have affected the vineyards but also the characteristics of the wine. In this research project, two natural factors were taken into account, temperature and annual precipitation. At times when machine learning had not yet been discovered, each process was very complicated and time-consuming. Therefore, machine learning is a very smart move to get fast and accurate results.Pearson correlation coefficient was used to come to a conclusion.hu_HU
dc.formatPDFhu_HU
enhu_HU
Prediction of wine quality using machine learning techniqueshu_HU
Open accesshu_HU
Óbudai Egyetemhu_HU
Budapesthu_HU
Bánki Donát Gépész és Biztonságtechnikai Mérnöki Karhu_HU
Óbudai Egyetemhu_HU
Műszaki tudományok - multidiszciplináris műszaki tudományokhu_HU
Temperaturehu_HU
Precipitationhu_HU
Winehu_HU
Pearson correlation coefficienthu_HU
Tudományos cikkhu_HU
Bánki Közleményekhu_HU
local.tempfieldCollectionsFolyóiratcikkekhu_HU
Kiadói változathu_HU
6 p.hu_HU
2. sz.hu_HU
6. évf.hu_HU
2024hu_HU
Óbudai Egyetemhu_HU


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