DocumentCode
3396895
Title
A joint of adaptive predictors for electric load forecasting
Author
Nastac, Dumitru I. ; Ulmeanu, Anatoli Paul ; Tuduce, Rodica ; Cristea, P.D.
Author_Institution
Univ. Politeh. of Bucharest, Bucharest, Romania
fYear
2013
fDate
7-9 July 2013
Firstpage
51
Lastpage
54
Abstract
This work describes a new approach of the adaptive retraining model for data forecasting. This time, six predictors are simultaneously employed in order to produce a better forecasting for electric load. By doing so, the new forecasting system eliminates iterative simulation. The set of predictors is regularly trained in order to be adjusted to the latest modifications of the input data. The new approach could be useful as a forecasting tool for a large variety of signals.
Keywords
load forecasting; neural nets; power engineering computing; prediction theory; adaptive predictors; adaptive retraining model; artificial neural network; data forecasting; electric load forecasting system; forecasting tool; Adaptation models; Artificial neural networks; Forecasting; Load modeling; Predictive models; Training; Vectors; artificial neural networks; electric load; forecasting; retraining;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on
Conference_Location
Bucharest
ISSN
2157-8672
Print_ISBN
978-1-4799-0941-4
Type
conf
DOI
10.1109/IWSSIP.2013.6623447
Filename
6623447
Link To Document