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