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http://dx.doi.org/10.5351/CKSS.2012.19.6.869

The Performance of Time Series Models to Forecast Short-Term Electricity Demand  

Park, W.G. (Digital Inclusion Policy Division, NIA)
Kim, S. (Department of Applied Statistics, Chung-Ang University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.6, 2012 , pp. 869-876 More about this Journal
Abstract
In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).
Keywords
Seasonal FARIMA; AR-GARCH; ARIMA; Holt-Winters; Electricity Demand;
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Times Cited By KSCI : 1  (Citation Analysis)
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