Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method
In this article, the authors propose an algorithmic approach to building a model of the dynamics of economic and, in particular, innovation processes. The approach under consideration is based on a complex algorithm that includes (1) decomposition of the time series into components using singular sp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/16/1/39 |
| _version_ | 1797447114171613184 |
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| author | Alexey F. Rogachev Alexey B. Simonov Natalia V. Ketko Natalia N. Skiter |
| author_facet | Alexey F. Rogachev Alexey B. Simonov Natalia V. Ketko Natalia N. Skiter |
| author_sort | Alexey F. Rogachev |
| collection | DOAJ |
| description | In this article, the authors propose an algorithmic approach to building a model of the dynamics of economic and, in particular, innovation processes. The approach under consideration is based on a complex algorithm that includes (1) decomposition of the time series into components using singular spectrum analysis; (2) recognition of the optimal component model based on fuzzy rules, and (3) creation of statistical models of individual components with their combination. It is shown that this approach corresponds to the high uncertainty characteristic of the tasks of the dynamics of innovation processes. The proposed algorithm makes it possible to create effective models that can be used both for analysis and for predicting the future states of the processes under study. The advantage of this algorithm is the possibility to expand the base of rules and components used for modeling. This is an important condition for improving the algorithm and its applicability for solving a wide range of problems. |
| first_indexed | 2024-03-09T13:50:08Z |
| format | Article |
| id | doaj.art-775269c3d67947d1a5301d7132d44088 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-09T13:50:08Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-775269c3d67947d1a5301d7132d440882023-11-30T20:51:33ZengMDPI AGAlgorithms1999-48932023-01-011613910.3390/a16010039Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis MethodAlexey F. Rogachev0Alexey B. Simonov1Natalia V. Ketko2Natalia N. Skiter3Faculty of Economics and Management, Department of Information Systems in Economics, Volgograd State Technical University, 400005 Volgograd, RussiaFaculty of Economics and Management, Department of Information Systems in Economics, Volgograd State Technical University, 400005 Volgograd, RussiaFaculty of Economics and Management, Department of Information Systems in Economics, Volgograd State Technical University, 400005 Volgograd, RussiaFaculty of Economics and Management, Department of Information Systems in Economics, Volgograd State Technical University, 400005 Volgograd, RussiaIn this article, the authors propose an algorithmic approach to building a model of the dynamics of economic and, in particular, innovation processes. The approach under consideration is based on a complex algorithm that includes (1) decomposition of the time series into components using singular spectrum analysis; (2) recognition of the optimal component model based on fuzzy rules, and (3) creation of statistical models of individual components with their combination. It is shown that this approach corresponds to the high uncertainty characteristic of the tasks of the dynamics of innovation processes. The proposed algorithm makes it possible to create effective models that can be used both for analysis and for predicting the future states of the processes under study. The advantage of this algorithm is the possibility to expand the base of rules and components used for modeling. This is an important condition for improving the algorithm and its applicability for solving a wide range of problems.https://www.mdpi.com/1999-4893/16/1/39singular spectrum analysisfuzzy logicinnovative activitytime serieseconomic developmentmodels |
| spellingShingle | Alexey F. Rogachev Alexey B. Simonov Natalia V. Ketko Natalia N. Skiter Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method Algorithms singular spectrum analysis fuzzy logic innovative activity time series economic development models |
| title | Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method |
| title_full | Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method |
| title_fullStr | Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method |
| title_full_unstemmed | Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method |
| title_short | Fuzzy Algorithmic Modeling of Economics and Innovation Process Dynamics Based on Preliminary Component Allocation by Singular Spectrum Analysis Method |
| title_sort | fuzzy algorithmic modeling of economics and innovation process dynamics based on preliminary component allocation by singular spectrum analysis method |
| topic | singular spectrum analysis fuzzy logic innovative activity time series economic development models |
| url | https://www.mdpi.com/1999-4893/16/1/39 |
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