DocumentCode :
3638960
Title :
ANN versus Grey theory based forecasting methods implemented on short time series
Author :
Jelena Milojković;Vaneo Litovski
Author_Institution :
Faculty of Electronic Engineering, University of Niš
fYear :
2010
Firstpage :
117
Lastpage :
122
Abstract :
Two modern concepts implemented for forecasting based on reduced time series are contrasted. Results obtained by use of artificial neural nets (ANNs), already discussed at this conference, are compared with the ones obtained by implementation of the so called Grey theory or Grey Model (GM). Particularly, feed-forward accommodated for prediction (FFAP) and time controlled recurrent (TCR) ANNs are used along with the GM(1,1) algorithm for one- and two-steps-ahead forecasting of various quantities (obsolete computers, electricity loads, number of fixed telephones etc). Advantages of the ANN concept are observed. The GM(1,1) was studied in the appendix and compared with no advantages against the least-mean-squares approximation by an exponential.
Keywords :
"Artificial neural networks","Forecasting","Time series analysis","Mathematical model","Neurons","Integrated circuit modeling","Computational modeling"
Publisher :
ieee
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2010 10th Symposium on
Print_ISBN :
978-1-4244-8821-6
Type :
conf
DOI :
10.1109/NEUREL.2010.5644094
Filename :
5644094
Link To Document :
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