The improvement of the intelligent decision support system for forecasting non-linear non-stationary processes

Authors

DOI:

https://doi.org/10.15587/2706-5448.2023.286516

Keywords:

forecasting, non-linear non-stationary processes, decision support system, data uncertainty, system analysis principles

Abstract

The paper is focused on solving the modern scientific and applied problem related to development and practical use in Decision Support Systems (DSS) of information technologies directed towards forecasting of non-linear non-stationary processes (NNP) that take place in economy and finances as well as in many other areas of activities. Thus, object of study are non-linear non-stationary processes taking place in economy and financial sphere.

The basic problem of the study is development of new mathematical models and methods of analysis and forecasting non-linear non-stationary processes in economy and finances, improvement of information decision support technologies that would help to enhance quality of forecast estimates and respective decisions in conditions of uncertainties and risk. The methods given in the paper are used for automating the process of intellectual data analysis that describe the processes under study and automatizing model constructing procedures.

As a result of the study performed the information technology was developed to be used in DSS based upon system analysis principles, taking into consideration possible data uncertainties, regression and intellectual data analysis. The technology provides for constructing adequate models of the process under study and computing high quality forecast estimates. The particular feature of the approach proposed is that it provides for high quality of experimental results due to taking into consideration special features of non-linear non-stationary processes that take place in various spheres of activities and their evolution is influenced by many specific factors.

The use of the technology proposed in decision support systems of enterprises, state governmental organs, and local self-government will create basis for effective solving the tasks of governing development of non-linear non-stationary processes that take place in many spheres of activities. The approaches proposed in the paper can be used in practice as separately as well as parts of existing information systems at enterprises and organizations.

Author Biographies

Petro Bidiuk, National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»

Doctor of Technical Science, Professor

Department of Mathematical Methods of System Analysis

Tetyana Prosyankina-Zharova, Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

PhD

Department of Application Informatics

Valerii Diakon, Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

PhD

Department of Application Informatics

Dmytro Diakon, Institute of Telecommunications and Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

Postgraduate Student

 Department of Application Informatics

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The improvement of the intelligent decision support system for forecasting non-linear non-stationary processes

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Published

2023-08-30

How to Cite

Bidiuk, P., Prosyankina-Zharova, T., Diakon, V., & Diakon, D. (2023). The improvement of the intelligent decision support system for forecasting non-linear non-stationary processes. Technology Audit and Production Reserves, 4(2(72), 37–46. https://doi.org/10.15587/2706-5448.2023.286516

Issue

Vol. 4 No. 2(72) (2023): Information and control systems

Section

Information Technologies

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Copyright (c) 2023 Petro Bidiuk, Tetyana Prosyankina-Zharova, Valerii Diakon, Dmytro Diakon

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