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dc.contributor.authorBaşaran Filik, Ümmühan
dc.contributor.authorFilik, Tansu
dc.contributor.editorCaetano, ND
dc.contributor.editorFelgueiras, MC
dc.contributor.editorForment, MA
dc.date.accessioned2019-10-21T20:11:52Z
dc.date.available2019-10-21T20:11:52Z
dc.date.issued2017
dc.identifier.issn1876-6102
dc.identifier.urihttps://dx.doi.org/10.1016/j.egypro.2016.12.147
dc.identifier.urihttps://hdl.handle.net/11421/20343
dc.description3rd International Conference on Energy and Environment Research (ICEER) -- SEP 07-11, 2016 -- Barcelona, SPAINen_US
dc.descriptionWOS: 000400640900040en_US
dc.description.abstractIn 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.sponsorshipUniv Poltecnica Catalunya, BarcelonaTECHen_US
dc.description.sponsorshipAnadolu University Scientific Research Projects Fund [1505F512]en_US
dc.description.sponsorshipThis work was supported by Anadolu University Scientific Research Projects Fund with project number: 1505F512.en_US
dc.language.isoengen_US
dc.publisherElsevier Science BVen_US
dc.relation.ispartofseriesEnergy Procedia
dc.relation.isversionof10.1016/j.egypro.2016.12.147en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWind Energyen_US
dc.subjectWind Speed Predictionen_US
dc.subjectArtificial Neural Networken_US
dc.titleWind Speed Prediction Using Artificial Neural Networks Based on Multiple Local Measurements in Eskisehiren_US
dc.typeconferenceObjecten_US
dc.relation.journal3rd International Conference On Energy and Environment Research, Iceer 2016en_US
dc.contributor.departmentAnadolu Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.identifier.volume107en_US
dc.identifier.startpage264en_US
dc.identifier.endpage269en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorBaşaran Filik, Ümmühan
dc.contributor.institutionauthorFilik, Tansu


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