Two-Sided Exponential Smoothing Method for Restoring of Dynamic Processes

Authors

DOI:

https://doi.org/10.20535/1810-0546.2016.6.80305

Keywords:

Restoring of dynamic processes regularities, Restoring of missed values of time series, Two-sided exponential smoothing, Exponential smoothing, Arithmetic mean, Autoregressive approach

Abstract

Background. Restoring of the true regularities and missed values of time series is an important stage of data preparation for the future modeling and forecasting, therefore development of new methods of restoring is needed.

Objective. To develop two-sided exponential smoothing method for restoring of regularities of dynamic processes evolution; to apply created method for restoring of missed values of London metal exchange average day prices for color metal (zinc) and to compare with methods of restoring by using arithmetic mean, autoregressive approach and exponential smoothing method.

Methods. To achieve the formulated goal the following methods were used: two-sided exponential smoothing method was created; restoring by using of arithmetic mean values with usage of known values; autoregressive approach and exponential smoothing.

Results. Two-sided exponential smoothing method was developed, which contains procedure of smoothing in direct and reversed time. The proposed method was used for restoring of dynamic processes and missed values of time series. Restoring of missed values of average daily prices for color metal (zinc) by making use of developed method and comparison with other methods were performed.

Conclusions. It is shown by means of simulation that two-sided exponential smoothing method is effective for restoring of process regularities. Developed method for restoring missing values of zinc prices in its application on practice showed an advantage in comparison with all the methods used in this study by the values of statistical characteristics of adequacy for constructed models, so it could be used in practice.

Author Biographies

Олена Вікторівна Братусь, Institute for Applied System Analysis, Igor Sikorsky NTUU “KPI”

Olena V. Bratus,

PhD student at the Department of mMathematical methods for system analysis

Володимир Миколайович Подладчіков, Institute for Applied System Analysis, Igor Sikorsky NTUU “KPI”

Volodymyr M. Podladchikov,

doctor of engineering sciences, professor at the Department of mMathematical methods for system analysis

Петро Іванович Бідюк, Institute for Applied System Analysis, Igor Sikorsky NTUU “KPI”

Petro I. Bidyuk,

doctor of engineering sciences, professor at the Department of mMathematical methods for system analysis

References

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Published

2016-12-27

Issue

Section

Art