Forecasting the power consumption of mines on the basis of stochastic time-series models
About authors
- 1 — Saint Petersburg State Mining Institute (Technical University)
- 2 — Saint Petersburg State Mining Institute (Technical University)
Abstract
The paper is devoted to building up time series models to forecast the power consumption of a mine. The results discussed are obtained using various linear filter models and artificial neural network. The wavelet transform of the raw time series is shown to be an efficient technique to increase the forecasting accuracy.
Область исследования:
(Archived) Geotechnical engineering, powerengineering and automation
Funding:
None
References
- Box G., Jenkins G. Time series analysis: Forecasting and control. Moscow. Mir, 1974. Vol. 1. 406 p.; Vol.2., 197 p.
- Galushkin A.IJ. Neural Networks Theory. Vol.1: Tutorial/IPRZR. Moscow, 2000. 416 р.
- Novikov L.V. Introductory wavelet signal analysis: Tutorial. Saint Petersburg: IAnP RAN, 1999. 152 р.
- Shumilova G.P., Gotman N.E., Startzeva T.B. Forecasting the power consumption of power grid on the basis of novel information technologies. Yekaterinburg: UrO RAN, 2002. 25 р.
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