Information technology of forecasting non-stationary time-series data using singular spectrum analysis

Authors

DOI:

https://doi.org/10.15587/1729-4061.2014.22158

Keywords:

time series, forecasting, information technology, singular spectrum analysis, phase space

Abstract

The information technology of forecasting non-stationary time series data, which cannot be reduced to stationary is proposed in the paper. Today, this time series class is often found in various fields, including economics, sociology, and is characterized by nonlinear trend, presence of several periodic components with variable frequency and amplitude, high noise level. Identification of non-stationary time series components is achieved using the method of singular spectrum analysis (SSA), which does not require a priori information about the time series structure. It is proposed to use several phase spaces, which can be constructed using different parameter of time window length in the SSA method, for building the models of predicting and identifying the most stable time series components. It is assumed that the time series is described by linear recurrence formulas, the coefficients of which are calculated in various phase spaces. Forecasting results are characterized by stability and efficiency as the non-stationary time series data analysis is performed in various states of the system and the most significant components are considered. The proposed information technology allows to select the amount of considered phase spaces in the forecasting model and their dimensions, as well as to make an effective short-term forecast of non-stationary time series data.

Author Biographies

Анна Александровна Чистякова, Kharkiv National University of Radio Electronics Lenina 16, Kharkov, 61166

Graduate student

Department of Information Control Systems

Борис Владимирович Шамша, Kharkiv National University of Radio Electronics Lenina 16, Kharkov, 61166

Professor

Department of Information Control Systems

References

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Published

2014-04-09

How to Cite

Чистякова, А. А., & Шамша, Б. В. (2014). Information technology of forecasting non-stationary time-series data using singular spectrum analysis. Eastern-European Journal of Enterprise Technologies, 2(4(68), 24–30. https://doi.org/10.15587/1729-4061.2014.22158

Issue

Vol. 2 No. 4(68) (2014): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2014 Анна Александровна Чистякова, Борис Владимирович Шамша

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