dc.contributor.author | Başaran Filik, Ümmühan | |
dc.contributor.author | Filik, Tansu | |
dc.contributor.editor | Caetano, ND | |
dc.contributor.editor | Felgueiras, MC | |
dc.contributor.editor | Forment, MA | |
dc.date.accessioned | 2019-10-21T20:11:52Z | |
dc.date.available | 2019-10-21T20:11:52Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 1876-6102 | |
dc.identifier.uri | https://dx.doi.org/10.1016/j.egypro.2016.12.147 | |
dc.identifier.uri | https://hdl.handle.net/11421/20343 | |
dc.description | 3rd International Conference on Energy and Environment Research (ICEER) -- SEP 07-11, 2016 -- Barcelona, SPAIN | en_US |
dc.description | WOS: 000400640900040 | en_US |
dc.description.abstract | In this study, artificial neural network (ANN) based models, which differently uses multiple local meteorological measurements together such as wind speed, temperature and pressure values, are proposed and it shown ANN based multivariable model's wind speed predictions can be improved for various cases. A data monitoring system are used which can sensitively measures in milliseconds time interval and records the values of weather temperature, wind speed, wind direction and weather pressure in this study. The proposed ANN based multivariable model's root mean square error (RMSE) and mean absolute error (MAE) performances are presented and compared for various cases. The effect of using multiple local variables instead of wind speed only are analyzed and compared with persistence method for benchmark. | en_US |
dc.description.sponsorship | Univ Poltecnica Catalunya, BarcelonaTECH | en_US |
dc.description.sponsorship | Anadolu University Scientific Research Projects Fund [1505F512] | en_US |
dc.description.sponsorship | This work was supported by Anadolu University Scientific Research Projects Fund with project number: 1505F512. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier Science BV | en_US |
dc.relation.ispartofseries | Energy Procedia | |
dc.relation.isversionof | 10.1016/j.egypro.2016.12.147 | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Wind Energy | en_US |
dc.subject | Wind Speed Prediction | en_US |
dc.subject | Artificial Neural Network | en_US |
dc.title | Wind Speed Prediction Using Artificial Neural Networks Based on Multiple Local Measurements in Eskisehir | en_US |
dc.type | conferenceObject | en_US |
dc.relation.journal | 3rd International Conference On Energy and Environment Research, Iceer 2016 | en_US |
dc.contributor.department | Anadolu Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü | en_US |
dc.identifier.volume | 107 | en_US |
dc.identifier.startpage | 264 | en_US |
dc.identifier.endpage | 269 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.contributor.institutionauthor | Başaran Filik, Ümmühan | |
dc.contributor.institutionauthor | Filik, Tansu | |