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• W3124984306 abstract "Today the problem of prediction of short-term electricity consumption or Short Term Load Forecasting (STLF), is a matter of capital importance for energy companies, since it allows more efficient management, allowing better use of equipment and resources. Demand prediction is a complex problem, since it is related to economic, climatic, temporal factors, and its behavior varies from one society to another. Each of these factors provides certain variables that can be represented in different ways, particularly the temporal ones. In this work, we hypothesize that the method used to present the temporal variables to a system of prediction of electrical consumption affects the results. To verify the hypothesis raised, we consider different methods of representing these variables, applied to the problem of predicting daily values of electricity consumption in the province of South East Anatolia, Turkey. The division of the temporary variable into day, day of the week, month and year variables individually for each period involved in the problem, proved to be the most convenient method, obtaining an improvement of up to 10.56% compared to other methods considered." @default.
• W3124984306 created "2021-02-01" @default.
• W3124984306 creator A5058600834 @default.
• W3124984306 date "2021-01-19" @default.
• W3124984306 modified "2023-09-26" @default.
• W3124984306 title "SHORT TERM LOAD ESTIMATION FOR ELECTRICITY CONSUMPTION OF SOUTH EAST ANATOLIA TURKEY" @default.
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• W3124984306 doi "https://doi.org/10.36222/ejt.862862" @default.
• W3124984306 hasPublicationYear "2021" @default.
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