Forecasting Türkiye's Hourly Electricity Production by Using Nonlinear Autoregressive Models

dc.creator	Özsoy, Mehmet
dc.date	2022-12-01T00:00:00Z
dc.date.accessioned	2025-02-25T10:38:43Z
dc.date.available	2025-02-25T10:38:43Z
dc.identifier	cfa18613-f9e7-4edb-a5e0-cbe570943ab2
dc.identifier	10.5281/zenodo.10406542
dc.identifier	https://avesis.sdu.edu.tr/publication/details/cfa18613-f9e7-4edb-a5e0-cbe570943ab2/oai
dc.identifier.uri	http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/101432
dc.description	<p><em style="color: rgba(0, 0, 0, 0.87); font-family: "Noto Sans", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Oxygen-Sans, Ubuntu, Cantarell, "Helvetica Neue", sans-serif; font-size: 14px;">Considering that industrialization is increasing rapidly, and technological enhancement is developing exponentially compared to the past, and considering that electrical energy is at the center of all these, it is one of the essentials of our age that this energy reaches its end users efficiently and at low cost. The aim of this study is to predict electricity generation with the help of the NARX model, an artificial neural network model, with the help of hourly data of Türkiye between 2016 and 2022 and to reveal the success of the model. As a result of the analysis, 99.83% coefficient of determination value was obtained with the NARX model.</em><br></p>
dc.language	eng
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Forecasting Türkiye's Hourly Electricity Production by Using Nonlinear Autoregressive Models
dc.type	info:eu-repo/semantics/article

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