Ідентифікація змінних параметрів моделі для побудови алгоритму прогнозування

An approach to identification of the mathematical expectation of acceleration of values change of data samples, which varies according to an unknown law, is presented in this article. An estimation method of mathematical expectation of values acceleration of change of data samples is developed, whic...

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Bibliographic Details
Date:2015
Main Authors: Bratus, E. V., Podladchikov, V. N.
Format: Article
Language:Ukrainian
Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2015
Online Access:http://journal.iasa.kpi.ua/article/view/54477
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Journal Title:System research and information technologies

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System research and information technologies
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Summary:An approach to identification of the mathematical expectation of acceleration of values change of data samples, which varies according to an unknown law, is presented in this article. An estimation method of mathematical expectation of values acceleration of change of data samples is developed, which is used to construct a forecasting algorithm based on the Kalman filter. An imitation modeling was performed, which showed the effectiveness of the suggested approach. The forecasting algorithm model based on the Kalman filter, autoregressive model and autoregressive moving average model are constructed using the daily average of the lead prices on the London Metal Exchange, and forecasting is done on the same data set. A comparative analysis of presented models, using the characteristics of forecasting values showed the advantage of the forecasting algorithm based on the Kalman filter.