Publication:
Forecasting Electricity Consumption with Neural Networks and Support Vector Regression

dc.contributor.authorsOgcu, Gamze; Demirel, Omer F.; Zaim, Selim
dc.contributor.editorOzsahin, M
dc.contributor.editorZehir, C
dc.date.accessioned2022-03-12T04:19:02Z
dc.date.accessioned2026-01-11T13:58:18Z
dc.date.available2022-03-12T04:19:02Z
dc.date.issued2012-10
dc.description.abstractEnergy strategy is extremely important for developing countries. As the economy of these countries grow rapidly, their energy consumptions increase substantially. Turkey's high growth rate in the last decade resulted with significant increase in energy consumption. Policy makers should give critical decisions and develop new strategies for meeting this growing energy demand. Apparently, accurate predictions of the future energy consumption are vital for developing such strategies. In this study, we have used the state of the art computation methods to forecast the electricity consumption of Turkey. The forecast results are compared with real consumption values to measure the performance of the methods.
dc.identifier.doi10.1016/j.sbspro.2012.09.1144
dc.identifier.issn1877-0428
dc.identifier.urihttps://hdl.handle.net/11424/223637
dc.identifier.wosWOS:000312875900172
dc.language.isoeng
dc.publisherELSEVIER SCIENCE BV
dc.relation.ispartof8TH INTERNATIONAL STRATEGIC MANAGEMENT CONFERENCE
dc.relation.ispartofseriesProcedia Social and Behavioral Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectElectricity consumption
dc.subjectForecasting
dc.subjectArtificial neural networks
dc.subjectSupport vector regression
dc.subjectENERGY DEMAND
dc.subjectTIME-SERIES
dc.subjectPREDICTION
dc.titleForecasting Electricity Consumption with Neural Networks and Support Vector Regression
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage1585
oaire.citation.startPage1576
oaire.citation.title8TH INTERNATIONAL STRATEGIC MANAGEMENT CONFERENCE
oaire.citation.volume58

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