Effectiveness Of Time Series Models In Predicting The Rate Of Electrical Energy Supplying The City Of Dohuk
DOI:
https://doi.org/10.25007/ajnu.v6n1a21Keywords:
SARMA, ARMA, Time series, Electricity of Duhok City, The seasonal multiplier modelAbstract
This paper deal with using time series models to study and analysis the monthly data on a rate of Electrical Power in Dohuk city for the period (2000-2013), estimating models,and The last twelve, which represents 2014 for the purposes of comparison with the predictions obtained.
The results of application show that the proper and efficiency model for representing time series data are the multiplicative seasonal model of order : ARMA(2,1)×SARMA(0,1)12 . According to estimation results of this model done forecasting to monthly rate of electrics capacity for year ahead from the period Jan. 2014 to Dec. 2014, these values show a harmonic direction with the same original time series. I've used Minitab and SPSS programs in the statistical aspect.
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المصادر باللغة الاجنبية
Karaman ,Abdullah S.:(2004).'An Experimental Study On Forecasting Using Tes Processes', Industrial and Systems Engineering Rutgers, University Piscataway, NJ08854, U.S.A.
Lendasse ,A., Bodt, E.DE, Wertz , V. and Vwrleysen, M.(2000), "Non-Linear Financial Time Series Forecasting-Application to The Bel 20 Stock Market Index", European Journal of Ecomoic and Social System 14 N ˚1(2000) 81-91.
Rojas ,I. and Pomares , H. (2004),"Soft-Computing Techniques for Time Series Forecasting ", ESANN 2004 Proceeding European Symposium on Artificial Neural Network-Bruges (Belgium), d-Side Publi., ISBN2-930307-04-8,pp. 93-102 .
Xuan , Tang , (2004), "Autoregressive Hidden Markor Model With Application in ELNINO Study ", Department of Mathematics and Statistics, University of Saskatchewan, Saskatoon.
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