Systems and Means of Informatics
2019, Volume 29, Issue 2, pp 12-30
MODELS OF DETECTION RELATIONSHIP BETWEEN TIME SERIES IN FORECASTING PROBLEMS
- K. R. Usmanova
- V. V. Strijov
Abstract
The problem of forecasting multiple time series requires detection of relationship between them. Engagement of related time series in a forecast model boosts the forecast quality. This paper introduces the convergent cross mapping (CCM) method used to detect a relationship between time series. This method estimates accuracy of reconstruction of one time series using the other series. The CCM method detects relationship between series not only in full trajectory spaces, but also in some trajectory subspaces. The computational experiment was carried out on two sets of time series: electricity consumption and air temperature, oil transportation volume and oil production volume.
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[+] About this article
Title
MODELS OF DETECTION RELATIONSHIP BETWEEN TIME SERIES IN FORECASTING PROBLEMS
Journal
Systems and Means of Informatics
Volume 29, Issue 2, pp 12-30
Cover Date
2019-05-30
DOI
10.14357/08696527190202
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
time series; forecasting; trajectory subspace; phase trajectory; convergent cross mapping
Authors
K. R. Usmanova  and V. V. Strijov , 
Author Affiliations
Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region, 141701, Russian Federation
Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation
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