NDLI: Enhancing the performances of a basic neural network tool for short-term forecasting of Italian electric load

Content Provider	IEEE Xplore Digital Library
Author	Lamedica, R. Mazzaro, M. Modesto, C. Prudenzi, A.
Copyright Year	1996
Description	Author affiliation: Dept. of Electr. Eng., Rome Univ., Italy (Lamedica, R.)
Abstract	In a previous study a basic multilayer perceptron artificial neural network for short-term forecasting of Italian hourly electric load has been implemented. The procedure has permitted adequate forecasting accuracies to be obtained for all the days with normal load conditions. However, the techniques adopted show some accuracy deficiencies while forecasting days with anomalous load conditions due to social factors (vacation periods, holidays, long weekends) and peculiar meteorological conditions as well. The paper illustrates the research activity conducted for enhancing the forecasting performances of the basic artificial neural network during these periods.
Starting Page	863
Ending Page	866
File Size	452609
Page Count	4
File Format	PDF
ISBN	0780331095
DOI	10.1109/MELCON.1996.551348
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-05-16
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Load forecasting Artificial neural networks Weather forecasting Predictive models Economic forecasting Social factors Meteorology Neurons Power industry
Content Type	Text
Resource Type	Article

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Enhancing the performances of a basic neural network tool for short-term forecasting of Italian electric load