The development of the method of evaluation of complex hierarchical systems based on improved alforitm of particle swarm
DOI:
https://doi.org/10.15587/2706-5448.2023.288055Keywords:
complex hierarchical real-time systems, responsiveness, particle swarm, global and local optimizationAbstract
The scientific task, which is solved in the research, is to increase the efficiency of the evaluation of complex hierarchical real-time systems. Finding solutions to nonlinear optimization problems and especially global optimization problems is one of the most popular problems in computational mathematics. In applied problems, the objective function, as a rule, has a large number of variables, is not given in an analytical form and is calculated as some integral characteristic of a complex dynamic process. The development of effective methods, to a certain extent adaptive to the variability of the objective function, is especially relevant in connection with the development of computer technology and the possibility of using parallel computing systems. The conducted research was aimed at developing a method of evaluating complex hierarchical systems based on an improved particle swarm. At the same time, the object of research was complex hierarchical real-time systems. The subject of research is the functioning of real-time hierarchical systems.
The novelties of the proposed method consist in:
‒ creating a multi-level and interconnected description of complex systems of hierarchical real-time systems;
‒ increasing the efficiency of decision making while evaluating complex systems of hierarchical real-time systems;
‒ solving the problem of falling into global and local extremes while assessing the state of complex systems of hierarchical real-time systems;
‒ the possibilities of directed search by several individuals of the particles swarm in a given direction, taking into account the degree of uncertainty;
‒ the possibilities of re-analysis of the state of complex systems of hierarchical real-time systems;
‒ avoiding the problem of loops while visualizing the state of the national security system in real time.
It is advisable to implement the specified method in specialized software, which is used to analyze the state of complex systems of hierarchical real-time systems and make management decisions.
References
- Shevchenko, A. I., Baranovskyi, S. V., Bilokobylskyi, O. V., Bodianskyi, Ye. V., Bomba, A. Ya. et al.; Shevchenko, A. I. (Ed.) (2023). Stratehiia rozvytku shtuchnoho intelektu v Ukraini. Kyiv: IPShI, 305.
- Shyshatskyi, A. V., Bashkyrov, O. M., Kostyna, O. M. (2015). Rozvytok intehrovanykh system zv’iazku ta peredachi danykh dlia potreb Zbroinykh Syl. Ozbroiennia ta viiskova tekhnika, 1 (5), 35–40.
- Ko, Y.-C., Fujita, H. (2019). An evidential analytics for buried information in big data samples: Case study of semiconductor manufacturing. Information Sciences, 486, 190–203. doi: https://doi.org/10.1016/j.ins.2019.01.079
- Ramaji, I. J., Memari, A. M. (2018). Interpretation of structural analytical models from the coordination view in building information models. Automation in Construction, 90, 117–133. doi: https://doi.org/10.1016/j.autcon.2018.02.025
- Pérez-González, C. J., Colebrook, M., Roda-García, J. L., Rosa-Remedios, C. B. (2019). Developing a data analytics platform to support decision making in emergency and security management. Expert Systems with Applications, 120, 167–184. doi: https://doi.org/10.1016/j.eswa.2018.11.023
- Chen, H. (2018). Evaluation of Personalized Service Level for Library Information Management Based on Fuzzy Analytic Hierarchy Process. Procedia Computer Science, 131, 952–958. doi: https://doi.org/10.1016/j.procs.2018.04.233
- Chan, H. K., Sun, X., Chung, S.-H. (2019). When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 125, 113114. doi: https://doi.org/10.1016/j.dss.2019.113114
- Osman, A. M. S. (2019). A novel big data analytics framework for smart cities. Future Generation Computer Systems, 91, 620–633. doi: https://doi.org/10.1016/j.future.2018.06.046
- Yeromina, N., Kurban, V., Mykus, S., Peredrii, O., Voloshchenko, O., Kosenko, V. et al. (2021). The Creation of the Database for Mobile Robots Navigation under the Conditions of Flexible Change of Flight Assignment. International Journal of Emerging Technology and Advanced Engineering, 11 (5), 37–44. doi: https://doi.org/10.46338/ijetae0521_05
- Rotshtein, A. P. (1999). Intellektualnye tekhnologii identifikatcii: nechetkie mnozhestva, geneticheskie algoritmy, neironnye seti. Vinnitca: UNIVERSUM, 320.
- Gödri, I., Kardos, C., Pfeiffer, A., Váncza, J. (2019). Data analytics-based decision support workflow for high-mix low-volume production systems. CIRP Annals, 68 (1), 471–474. doi: https://doi.org/10.1016/j.cirp.2019.04.001
- Harding, J. L. (2013). Data quality in the integration and analysis of data from multiple sources: some research challenges. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-2/W1, 59–63. doi: https://doi.org/10.5194/isprsarchives-xl-2-w1-59-2013
- Gorelova, G. V. (2013). Kognitivnyi podkhod k imitatcionnomu modelirovaniiu slozhnykh sistem. Izvestiia IuFU. Tekhnicheskie nauki, 3, 239–250.
- Orouskhani, M., Orouskhani, Y., Mansouri, M., Teshnehlab, M. (2013). A Novel Cat Swarm Optimization Algorithm for Unconstrained Optimization Problems. International Journal of Information Technology and Computer Science, 5 (11), 32–41. doi: https://doi.org/10.5815/ijitcs.2013.11.04
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Andrii Shyshatskyi, Tetiana Pluhina, Ganna Plekhova, Anzhela Binkovska, Sergii Pronin, Tetiana Stasiuk, Oleksii Nalapko, Nadiia Protas, Tetiana Pliushch, Dmytro Burlak
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.