Application of Soft Computing Models to Daily Average Temperature Analysis

dc.contributor.authorGöçken, Mustafa
dc.contributor.authorBoru, Aslı
dc.contributor.authorDosdoğru, Ayşe Tuğba
dc.contributor.authorBerber, Nafiz
dc.date.accessioned2018-12-11T10:32:39Z
dc.date.available2018-12-11T10:32:39Z
dc.date.issued2015-02-02
dc.descriptionDOI: 10.19072/ijet.105706en_US
dc.description.abstractProviding critical information about daily life, weather forecasting has important role for human being. Especially, temperature forecasting is rather important because it affects not only people but also other atmospheric parameters. Various techniques have been used for analysis of the dynamic behaviour of weather. This ranges from simple observation of weather to using computer technology. In this study, ANFIS (Adaptive Network Based Fuzzy Inference System), ANN (Artificial Neural Network) and MRA (Multiple Regression Analysis) have been applied for weather forecasting. To judge the forecasting capability of the proposed models, the graphical analysis and the indicators of the accuracy of Mean Absolute Deviation (MAD), Mean Square Error (MSE), Root-Mean Squared Error (RMSE), Mean Absolute Percent Error (MAPE), Determination Coefficient (R2), Index of Agreement (IA), Fractional Variance (FV), Coefficient of Variation (CV, %) are given to describe models’ forecasting performance and the error. The results show that ANFIS exhibited best forecasting performance on weather forecasting compared to ANN and MRA.en_US
dc.identifier.issn2149-0104
dc.identifier.issn2149-5262
dc.identifier.urihttps://hdl.handle.net/11363/485
dc.language.isoenen_US
dc.publisherİstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Pressen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Yayınıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectResearch Subject Categories::TECHNOLOGYen_US
dc.titleApplication of Soft Computing Models to Daily Average Temperature Analysisen_US
dc.typeArticleen_US

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