Kantsedal H. Adaptive control of impulse processes with multirate sampling in cognitive maps of cryptocurrency usage

Українська версія

Thesis for the degree of Doctor of Philosophy (PhD)

State registration number

0825U001991

Thesis Registration Form

0825U001991.pdf

Applicant for

Specialization

  • 124 - Системний аналіз

Specialized Academic Board

PhD 9372

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

Essay

The dissertation examines the modeling and management of cryptocurrency exchange rate instability using cognitive maps and impulse processes.The focus is on constructing impulse process models in cognitive maps with multi-rate discretization for managing cryptocurrency exchange rates, particularly their stabilization. Adaptive control methods have been employed to mitigate the disadvantages of cryptocurrency usage and stabilize cryptocurrency markets. The aim of the study is to develop mathematical models and control methods for analyzing the dynamics of cryptocurrency markets using cognitive maps. The first chapter provides a comprehensive analysis of the current state of cryptocurrency usage in financial systems and examines key issues associated with their application. In the second chapter, a cognitive map was developed to model the interconnections between key factors influencing cryptocurrency prices in financial markets. In the third chapter, a coordination control system for managing coordinate ratios in the cognitive map of the cryptocurrency market was developed, along with methods for identifying adjacency matrices in the impulse process model with multi-rate discretization. To maintain an optimal ratio of key economic parameters characteristic of asset trading on exchanges, a coordination control system was designed. The fourth chapter presents practical verification of theoretical concepts developed in previous chapters. It includes modeling results of impulse processes in mining cognitive maps and cognitive maps of cryptocurrency use in financial markets. The research findings have significant practical value for analyzing and managing the cryptocurrency market. The developed cognitive map models enable the assessment of various economic, technological, and speculative factors influencing cryptocurrency prices, which can be used for price forecasting and market stabilization. The modified algorithms for identifying cognitive map weight coefficients can be applied in financial forecasting, trading bots, and automated asset management systems.

Read more

Research papers

Романенко В. Д., Мілявський Ю. Л., Канцедал Г. О. Адаптивна система стабілізації нестійкого курсу криптовалюти на основі моделі імпульсного процесу когнітивної карти. Проблеми управління та інформатики. 2021. № 2. С. 11-23. DOI: 10.34229/1028-0979-2021-2-2

Канцедал Г. О. Ідентифікація матриці суміжності у моделі імпульсних процесів з різнотемповою дискретизацією в когнітивній карті застосування криптовалют. Проблеми керування та інформатики. 2022. № 4. С. 35-48.DOI: 10.34229/1028-0979-2025-1-8

Romanenko V. Kantsedal H. Systematic studies of cryptocurrency usage tools for financial markets. System research and information technologies. 2024. №4. P. 14-31.DOI:10.20535/SRIT.2308-8893.2024.4.01

Romanenko V., Miliavskyi Y., Kantsedal H. Stabilization of impulse processes of the cognitive map of cryptocurrency usage with multirate sampling and coordination between some nodes parameters. System Analysis and Artificial Intelligence / Ed. Zgurovsky M., Pankratova N. New York: Springer, Vol 1107, 2023. P. 83-100.DOI: 10.1007/978-3-031-37450-0_5

Romanenko V., Miliavskyi Y., Kantsedal H. Application of impulse process models with multirate sampling in cognitive maps of cryptocurrency for dynamic decision making. System Analysis & Intelligent Computing. Theory and Applications. IEEE International Conference on System Analysis & Intelligent Computing / Ed. Zgurovsky M., Pankrarova M. New York: Springer, 2022. Vol. 1022. P. 115-137.DOI: 10.1007/978-3-030-94910-5_7

Romanenko V., Miliavskyi Y., Kantsedal G. Dynamic decisionmaking for cryptocurrency rate stabilization based on the impulse process model in the cognitive map. International conference Problems of decision making under uncertainties (PDMU-2021) : Abstracts of XXXVII conference (Skhidnytsia, 11-15 May 2021), Kyiv : Taras Shevchenko National University of Kyiv, 2021. P. 88-89.

Romanenko V., Kantsedal H., Milyavsky Y. Identification of cognitive maps weights in the multirate model of cryptocurrency application. International conference Problems of decision making under uncertainties (PDMU-2022) : Abstracts of XXXVII conference. (Sheki-Lankaran, 23 – 25 Nov. 2022). Kyiv : Taras Shevchenko National University of Kyiv, 2022. P. 96-97.

Romanenko V., Miliavskyi Yu., Kantsedal H. Coordination of nodes parameters ratios of the cryptocurrency usage cognitive map based on impulse process models with multirate sampling. International conference Problems of decision making under uncertainties (PDMU-2023) : Abstracts of XXXVII conference (Polyana, 11-15 Sept. 2023), Kyiv : Taras Shevchenko National University of Kyiv, 2023. P. 89-90.

Romanenko V., Miliavskyi Y., Kantsedal H. Constrained disturbances suppression for multirate impulse processes in cognitive maps of cryptocurrency applications. International conference problems of Decision making under uncertainties (PDMU-2024) : Abstracts of XXXIX conference (Brono, 9-10 Sept. 2024), Kyiv : Taras Shevchenko National University of Kyiv, 2024. P. 114 - 115.

Romanenko V., Miliavskyi Y., Kantsedal H. Automated control problems for dynamic processes applied to cryptocurrency in finansial markets. Recent developments in automatic control systems / Ed. Kondratenko Y., Kuntsevich V., Chikrii A., Gubarev Y. London: River Publishers, 2024. P. 417-444.DOI: 10.1201/9781003339229

Read more

Files

autoreferat-анотація_Канцедал.docx

дисертація 20-03 Канцедал.pdf

Similar theses

0826U000137

Oleksii S. Serhieiev

Models and methods of decision-making for material flow analysis and planning in medical logistics systems

0825U004194

Svitlana V. Kozyr

Management of dual education development projects portfolio based on evolutionary methods

0825U003241

Dmytro Shmundiak

System analysis of the state of natural environments considering anomalies

0825U002260

Nikita O. Mykhailov

Machine Learning Algorithms for Developing High-Efficiency Project Management Systems

0825U001678

Andrii M. Tytarenko

Deep reinforcement learning for caregiving robotics