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dc.contributor.authorEmeksiz, Cem
dc.contributor.authorDemir, Gülden
dc.date.accessioned2021-03-19T17:40:39Z
dc.date.available2021-03-19T17:40:39Z
dc.date.issued2018
dc.identifier.issn2147-6799
dc.identifier.issn2147-6799
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TXpBM09USTRPQT09
dc.identifier.urihttps://hdl.handle.net/20.500.12881/12793
dc.description.abstractWind speed is the most important parameter of the wind energy conversion system. Therefore temperature, humiditiy and pressure data, which has significant effect on the wind speed, have become extremely important. In the literature, various models have been used to realize the wind speed estimation. In this study; Six different data mining algorithms were used to determine the effect of meteorological parameters on wind speed estimation. The data were collected from the measurement station established on the campus of Gaziosmanpaşa University. We focused on the bagging algorithm to determine the appropriate combination of wind speed estimates. The bagging algorithm was used for the first time in estimation of wind speed by taking into account meteorological parameters. To find the most efficiency method on such problem 10-fold cross validation technique was used for comparision. From results, It is concluded that bagging algorithm and temperature-humiditiy-pressure combination showed the best performance. Additionaly, temperature and pressure data are more effective in the wind speed estimation.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBilgisayar Bilimleri, Yapay Zekaen_US
dc.titleAn Investigation of the Effect of Meteorological Parameters on Wind Speed Estimation Using Machine Learning Algorithmsen_US
dc.typearticleen_US
dc.relation.journalInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.contributor.departmentGaziosmanpaşa Üniversitesien_US
dc.identifier.volume6en_US
dc.identifier.issue4en_US
dc.identifier.startpage311en_US
dc.identifier.endpage321en_US
dc.contributor.institutionauthor[0-Belirlenecek]
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanen_US


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