Загальна методика прогнозування нелінійних нестаціонарних процесів на основі математичних моделей з використанням статистичних даних

The article considers the problem of forecasting nonlinear nonstationary processes, presented in the form of time series, which can describe the dynamics of processes in both technical and economic systems. The general technique of analysis of such data and construction of corresponding mathematical...

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Bibliographic Details
Date:2021
Main Authors: Belas, Oleg, Belas, Andrii
Format: Article
Language:Ukrainian
Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2021
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Online Access:http://journal.iasa.kpi.ua/article/view/236713
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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:The article considers the problem of forecasting nonlinear nonstationary processes, presented in the form of time series, which can describe the dynamics of processes in both technical and economic systems. The general technique of analysis of such data and construction of corresponding mathematical models based on autoregressive models and recurrent neural networks is described in detail. The technique is applied on practical examples while performing the comparative analysis of models of forecasting of quantity of channels of service of cellular subscribers for a given station and revealing advantages and disadvantages of each method. The need to improve the existing methodology and develop a new approach is formulated.