Forecasting based on short time series using ANNs and grey theory - some basic comparisons

Authors:
Jelena Milojković;Vančo Litovski;Octavio Nieto-Taladriz;Slobodan Bojanić
Affiliations:
University of Niš, Faculty of Electronic Engineering, Aleksandra Medvedeva, Niš, Serbia;University of Niš, Faculty of Electronic Engineering, Aleksandra Medvedeva, Niš, Serbia;Universidad Politécnica de Madrid, ETSIT, Madrid, Spain;Universidad Politécnica de Madrid, ETSIT, Madrid, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Year:
2011

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Abstract

Two modern forecasting methods based on short time series are compared. Results obtained by use of artificial neural nets (ANNs), are contrasted to the ones produced by use of the so called grey theory or Grey Model (GM). Specifically, the Feed-Forward Accommodated for Prediction (FFAP) and the Time Controlled Recurrent (TCR) ANNs are used along with the GM(1,1) algorithm for one- and two-steps-ahead forecasting of various quantities (electricity loads, number of fixed telephones lines, obsolete computers, etc). Advantages of the ANN concept are observed.