Forecasting Based on Short Time Series Using ANNs and Grey Theory – Some Basic Comparisons

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...

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Bibliographic Details
Published inAdvances in Computational Intelligence pp. 183 - 190
Main Authors Milojković, Jelena, Litovski, Vančo, Nieto-Taladriz, Octavio, Bojanić, Slobodan
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2011
SeriesLecture Notes in Computer Science
Subjects
ANNs
forecasting
Grey theory
prediction
short time series
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Summary: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.
ISBN:9783642215001
3642215009
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-21501-8_23