| Autor: |
Lev Raskin, Larysa Sukhomlyn, Dmytro Sagaidachny, Roman Korsun |
| Jazyk: |
English<br />Ukrainian |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Сучасні інформаційні системи, Vol 5, Iss 4 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2522-9052 |
| DOI: |
10.20998/2522-9052.2021.4.11 |
| Popis: |
Known technologies for analyzing Markov systems use a well-operating mathematical apparatus based on the computational implementation of the fundamental Markov property. Herewith the resulting systems of linear algebraic equations are easily solved numerically. Moreover, when solving lots of practical problems, this numerical solution is insufficient. For instance, both in problems of structural and parametric synthesis of systems, as well as in control problems. These problems require to obtain analytical relations describing the dependences of probability values of states of the analyzed system with the numerical values of its parameters. The complexity of the analytical solution of the related systems of linear algebraic equations increases rapidly along with the increase in the system dimensionality. This very phenomenon manifests itself especially demonstratively when analyzing multi-threaded queuing systems. Accordingly, the objective of this paper is to develop an effective computational method for obtaining analytical relations that allow to analyze high-dimensional Markov systems. To analyze such systems this paper provides for a decomposition method based on the idea of phase enlargement of system states. The proposed and substantiated method allows to obtain analytical relations for calculating the distribution of Markov system states. The method can be effectively applied to solve problems of analysis and management in high-dimensional Markov systems. An example has been considered |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
