Estimation of global solar radiation on horizontal surface using meteorological data

dc.contributor.authorGürel, Ali Etem
dc.contributor.authorErgün, Alper
dc.date.accessioned2020-05-01T12:11:55Z
dc.date.available2020-05-01T12:11:55Z
dc.date.issued2012
dc.departmentDÜ, Düzce Meslek Yüksekokulu, Elektrik ve Enerji Bölümüen_US
dc.descriptionGurel, Ali Etem/0000-0003-1430-8041en_US
dc.descriptionWOS: 000297087600043en_US
dc.description.abstractIn the present study, the methods of Artificial Neural Networks (ANN) and Regression Analysis were used in estimating monthly average daily global solar radiation arriving on horizontal surface in Rize with the help of meteorological and geographic data like monthly average daily extraterrestrial radiation, monthly average daily hours of bright sunshine, day length, relative humidity, wind speed, temperature and declination angle. Mean bias error (MBE), root mean square error (RMSE) and t-statistic methods were used to evaluate performance of the estimation. It was seen at the end of the study that the equation obtained through multi-regression analysis method yielded better performance than that of obtained through ANN method.en_US
dc.identifier.endpage948en_US
dc.identifier.issn1308-772X
dc.identifier.issue2en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage941en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/6270
dc.identifier.volume28en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSila Scienceen_US
dc.relation.ispartofEnergy Education Science And Technology Part A-Energy Science And Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectRegression analysisen_US
dc.subjectMeteorological dataen_US
dc.titleEstimation of global solar radiation on horizontal surface using meteorological dataen_US
dc.typeArticleen_US

Dosyalar