Application of artificial intelligence methods to forecast electric energy monthly sales in rural areas

Małgorzata Trojanowska

Akademia Rolnicza w Krakowie

Jerze Małopolski

Akademia Rolnicza w Krakowie


Abstract

In this paper the possibilities of application artificial intelligence to forecast electric energy monthly sales to rural receivers were presented. There were three models which were built on the basis of determinate chaos theory, artificial neural networks and fuzzy set theory. Calculations proved that artificial neural networks are good enough to forecast the demand for the supplies of electricity. Fuzzy Takagi-Sugeno model is competetive in comparison with neural model and worth recommending to forecasting.

Keywords:

electric energy, forecast, chaos theory, neural networks, fuzzy sets

Findeisen W., Szymanowski J., Wierzbicki A., 1977. Teoria i metody obliczeniowe optymalizacji. WNT Warszawa.

Osowski S., 1996. Sieci neuronowe w ujęciu algorytmicznym. WNT Warszawa.

Piegat A., 1999. Modelowanie i sterowanie rozmyte. AOW EXIT Warszawa.

Prognozowanie w elektroenergetyce. Zagadnienia wybrane. Red. I. Dobrzańska. 2002. Wyd. Pol. Częstoch., Częstochowa.

Yager R. R., Filev D. P., 1995. Podstawy modelowania i sterowania rozmytego. WNT Warszawa.


Published
2004-12-31



Małgorzata Trojanowska 
Akademia Rolnicza w Krakowie
Jerze Małopolski 
Akademia Rolnicza w Krakowie



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