Oleg Sova

@viti.edu.ua

Information Technology Faculty, ACS Department
Military Institute of Telecommunications and Information Technologies named after Kruty Heroes

Oleg Sova


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https://researchid.co/oleg_sova

RESEARCH INTERESTS

Cloud technologies, artificial intelligence, management systems, data processing
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Scopus Publications

Scopus Publications

  • DEVELOPMENT OF A SCIENTIFIC AND METHODOLOGICAL APPARATUS FOR ENSURING THE FUNCTIONAL RELIABILITY OF SPECIAL-PURPOSE INFORMATION SYSTEMS
    Oleh Shknai, Illia Dmytriiev, Oleg Sova, Andrii Shyshatskyi, Olesia Zhuk, et al.
    Intelligent Decision Support Systems Methods for Optimizing and Supporting Management Decisions Collective Monograph, 2026
    The object of research is special-purpose information systems (IS). The problem addressed in the study is the improvement of the functional reliability of special-purpose IS. The development of a scientific and methodological apparatus for providing a functional special-purpose IS was carried out. The originality of the research consists of:– systematic assessment of the state of functional reliability of special-purpose IS using the proposed principles of its provision;– construction of multidimensional dependencies of the state of functional reliability of the special-purpose IS, which achieves an assessment of the functional reliability of the IS based on an arbitrary number of indicators;– in the assessment of the functional reliability of special-purpose IS using the joint use of measurement data and fuzzy expert assessments, which solves the problem of dimensionality;– in the construction of the time dependence of changes in indicators that characterize the state of functional reliability of special-purpose IS, which allows determining the moments of deviation of their values from the nominal ones.In the assessment of the functional reliability of information services based on the concept of profiles, which achieves the possibility of decentralized influence on the special-purpose IS to increase its functional reliability.In reducing uncertainty about the state of functional reliability of special-purpose IS, due to the use of an appropriate approach in the method of assessing the functional reliability of information services based on the concept of profiles.The proposed scientific and methodological apparatus provides an increase in the efficiency of assessing the functional reliability of the IS by an average of 40%, while ensuring high reliability of the obtained results at the level of 92%, which is confirmed by the results of a numerical experiment.
  • THE CREATION OF A METHODOLOGY FOR INTELLIGENT ASSESSING AND MANAGING THE SECURITY STATE OF COMPLEX SYSTEMS
    Hennadii Miahkykh, Oleg Sova, Olha Salnikova, Oleksandr Zhuk, Iraida Stanovska, et al.
    Eastern European Journal of Enterprise Technologies, 2026
    Complex technical systems are the object of the study. The problem that is solved in the study is an increase in the level of security of complex technical systems. The originality of the study consists in: – comprehensive assessment of the security state of complex technical systems due to multi-level assessment using the theory of artificial intelligence; – reduced error in assessing the security state of a complex technical system due to the human factor due to the verification of the parameters of a complex technical system; – selection of the best individuals in bio-inspired algorithms, due to the use of an improved genetic algorithm, which achieves an increase in the efficiency and reliability of the obtained decisions and evaluations; – make accurate decisions by individually adjusting the actions of agents in each bio-inspired algorithm; – eliminating the conflict between agents in improved bio-inspired algorithms, which increases the efficiency and reliability of decisions made regarding the security state of complex technical systems; – implementation of deep learning of knowledge bases of agents of each bio-inspired algorithm, due to the method of deep learning, which achieves an increase in the efficiency and reliability of assessments and control effects on the security state of complex technical systems. Modeling of the proposed methodology was carried out, during which it was established that increasing the security of complex technical systems is achieved by increasing the efficiency of decision-making at the level of 15−17% due to the use of additional procedures and ensuring the reliability of decisions made at the level of 0.91. This study can be used in practice when taking into account the delay time for collecting and proving information from sensors (sensors) of complex technical systems.
  • A SET OF METHODS FOR ENHANCING THE EFFICIENCY OF INFORMATION PROCESSING IN INTELLIGENT DECISION SUPPORT SYSTEMS
    Oleh Shknai, Oleg Sova, Olena Nechyporuk, Oleksii Nalapko, Oleksiy Buyalo, et al.
    Decision Support Systems Mathematical Support, 2025
    This section of the study proposes a set of methods to enhance the efficiency of information processing in intelligent decision support systems.The authors suggest the following methods:– a method for managing information flows in intelligent decision support systems using a population-based algorithm;– a method for evaluating the timeliness of processing diverse data types in decision support systems;– a method for assessment and forecasting in intelligent decision support systems.The novelty of the proposed methods lies in:– determining the initial population of agents and their starting positions in the search space by considering the degree of uncertainty in the initial data about information flows within intelligent decision support systems;– accounting for the initial velocity of each agent, which enables prioritization of search tasks within the respective search space;– universality of agent feeding search strategies, allowing the classification of conditions and factors that influence the management of information flows in intelligent decision support systems;– ability to explore solution spaces described by atypical functions through the application of agent movement technique selection procedures;– capability to search for solutions simultaneously in multiple directions;– potential for deep learning of agents' knowledge bases;– ability to calculate the required amount of computational resources to be engaged in cases where existing resources are insufficient for necessary computations;– consideration of the type of uncertainty in the data circulating within decision support systems;– implementation of adaptive strategies for solution space searches by the population agents;– prioritization of search tasks by population agents;– initial placement of population members considering the type of uncertainty;– application as a universal tool for analyzing the timeliness of processing diverse data types in decision support systems;– verification of the adequacy of the obtained results;– avoidance of the local extremum problem;– use of a new type of fuzzy cognitive temporal models focused on multidimensional analysis and forecasting of object states under conditions of uncertainty;– ability to combine elements of artificial neural networks;– capability to train individual elements of artificial neural networks;– data computation within a single epoch without the need to store previous calculations;– prevention of error accumulation during the training of artificial neural networks as a result of processing incoming information.
  • DEVELOPMENT OF THE METHOD OF MULTI-CRITERIA EVALUATION OF HIERARCHICAL SYSTEMS
    Oleg Sova, Oleksandr Stanovskyi, Taras Hurskyi, Valentyn Olshanskyi, Oleksandr Volkov, et al.
    Eastern European Journal of Enterprise Technologies, 2025
    Multicriteria evaluation offers undeniable advantages over single-criterion assessment methods. The object of the study is hierarchical systems. The subject of the study is the process of multicriteria evaluation of the state of hierarchical systems. A method for multicriteria evaluation of hierarchical systems is proposed. The originality of the method lies in the application of additional advanced procedures that allow for the following: – verification of input data and refinement of inter-element connections within the hierarchical system using an enhanced penguin swarm algorithm. This minimizes the risk of errors resulting from incorrect data input in the assessment of the operational military (force) grouping; – description of external and internal factors affecting the hierarchical system subject to multicriteria evaluation through the use of fuzzy cognitive models; – adaptation to the type of hierarchical system via multilevel adjustment of the system of indicators and evaluation criteria; – reduction of uncertainty through the use of interval-valued Pythagorean fuzzy sets, thereby improving the reliability of multicriteria assessment of hierarchical system states; – identification of the most vulnerable elements within the hierarchical system using a fault tree analysis; – adaptation of the membership function type depending on the system’s available computational resources, which ensures compatibility with existing computational capacities. An example of the method’s application is demonstrated through the multicriteria evaluation of an operational military (force) grouping. The proposed method provides an average improvement of 35% in accuracy and efficiency, while ensuring a high convergence rate of results at the level of 93.17%
  • DEVELOPMENT OF HETEROGENEOUS DATA PROCESSING METHOD IN ORGANIZATIONAL AND TECHNICAL SYSTEMS
    Salman Rasheed Owaid, Svitlana Kashkevich, Andrii Shyshatskyi, Hryhorii Radzivilov, Oleg Sova, et al.
    Eastern European Journal of Enterprise Technologies, 2025
    The object of the study is heterogeneous data in organizational-technical systems. The subject of the study is the process of heterogeneous data processing. The problem of this study is enhancing the efficiency of heterogeneous data processing in organizational-technical systems while ensuring a predefined level of reliability, regardless of the volume of incoming data. A method for heterogeneous data processing in organizational-technical systems has been developed. The originality of the method lies in the use of additional improved procedures, which allow: – achieving the placement of the initial population of agents in the combined algorithm swarm and their initial position in the search space, considering the uncertainty level of input data circulating in the organizational-technical system. This is achieved using correction coefficients; – accounting for the initial velocity of each agent in the combined algorithm swarm, enabling search prioritization in the corresponding search space (across elements and components of the organizational-technical system); – determining the feasibility of decisions in heterogeneous data processing, considering external factors, which reduces the solution search time; – ability to calculate the required computational resources, determining the additional resources needed in case existing computational capacity is insufficient. A practical implementation of the proposed method was tested on heterogeneous data processing in an operational military task force, demonstrating: a 14–20 % increase in decision-making efficiency due to the integration of additional procedures; a decision reliability level maintained at 0.9
  • DEVELOPMENT OF A SOLUTION SEARCH METHOD USING A COMBINED BIO-INSPIRED ALGORITHM
    Khudhair Abed Thamer, Oleg Sova, Olena Shaposhnikova, Volodymyr Yashchenok, Iraida Stanovska, et al.
    Eastern European Journal of Enterprise Technologies, 2024
    The object of the study is decision support systems. The subject of the study is the decision-making process in management problems using a combined bio-inspired algorithm, consisting of: – the improved wolf optimization algorithm and the improved sparrow search algorithm – for solving optimization problems regarding the object state; – an advanced genetic algorithm – for selecting the best agents in flocks; – an advanced training method – for deep training of agents to improve the optimization characteristics of agents. A solution search method using an improved bio-inspired algorithm is proposed. The method has the following sequence of actions: – input of initial data; – initialization of the search for a flock of sparrows and its parameters; – ranking and selection of sparrow agents using an advanced genetic algorithm; – updating the sparrow location for the discoverer; – checking the conditions for updating the position of sparrows; – initialization of additional search parameters; − running the gray wolf optimization algorithm; – training agents’ knowledge bases; – determining the amount of necessary computing resources of the intelligent decision support system. The originality of the proposed method lies in the combined use of bio-inspired algorithms, setting agents taking into account the uncertainty of the initial data, advanced global and local search procedures. The method makes it possible to increase the efficiency of data processing at the level of 19 % using additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interest of solving national security problems
  • DEVELOPMENT OF A METHOD FOR MANAGING TECHNICAL SYSTEMS USING A BIO-INSPIRED ALGORITHM
    Oleg Sova, Illia Dmytriiev, Nina Kuchuk, Oleksandr Yefymenko, Nataliia Lytvynenko, et al.
    Eastern European Journal of Enterprise Technologies, 2024
    Today’s management solutions depend precisely on the successful solution of optimization problems, which are discontinuous, undifferentiated and multimodal. One of the approaches to increase the efficiency of solving optimization problems is bio-inspired algorithms. The object of the study is complex dynamic objects. The subject of the study is the decision-making process in the problems of managing complex dynamic objects. A management method using a bio-inspired algorithm is proposed. The research is based on the goose algorithm – for finding a solution to the state of dynamic objects with a hierarchical structure. Evolving artificial neural networks are used to train goose agents (GA) and an advanced genetic algorithm is used to select the best ones in the combined swarm algorithm. The originality of the proposed method lies in setting GA taking into account the uncertainty of the initial data, improved global and local search procedures. Also, the originality of the study lies in determining GA food locations, which allows choosing the priority of search in a given direction. The next element in the originality of the study is the ability to determine the indicators of guard GA, which allows adjusting the amount of time during which the GA flock will be located. Another original element of the study is the determination of the initial velocity of each GA. This makes it possible to optimize the speed of conducting exploration by each GA in a certain research direction. The method allows increasing the efficiency of data processing at the level of 10–12 % by using additional improved procedures. The proposed method should be used to solve problems of evaluating complex dynamic objects
  • DEVELOPMENT OF A METHOD FOR MANAGING A GROUP OF UNMANNED AERIAL VEHICLES USING A POPULATION ALGORITHM
    Mohammed Jasim Abed Alkhafaji, Svitlana Kashkevich, Andrii Shyshatskyi, Oleg Sova, Oleksii Nalapko, et al.
    Eastern European Journal of Enterprise Technologies, 2024
    The object of the study is a group of unmanned aerial vehicles (UAVs). The subject of the study is the decision-making process in management tasks using: – an improved brown bear algorithm (BBA), which achieves the determination of the optimal UAV movement route based on the given optimization criterion (the probability of completing the flight task), described by complex multimodal functions; – evolving artificial neural networks for deep learning of the multi-agent system knowledge base, by training both the parameters and the architecture of artificial neural networks. The originality of the method lies in using additional improved procedures that allow: – the initial BBA population and their initial position on the search plane are determined considering the degree of uncertainty in the data on the UAV group movement route; – the initial speed of each BBA is considered, enabling the prioritization of searches in the respective search plane (height, latitude, and longitude); – the suitability of the UAV group's flight route for performing the flight task is determined, considering a set of external factors, thereby reducing the decision search time; – the universality of BBA food search strategies allows classifying a set of conditions and factors affecting the completion of the flight task. This aids in identifying the most feasible movement options for the UAV group based on the defined optimization criterion for movement route. Modeling the operation of the proposed method has shown that the increase in decision-making efficiency reaches 15–18 %. The enhancement in the method's efficiency is achieved through additional procedures and ensuring the reliability of the decisions at a level of 0.9
  • DEVELOPMENT OF A METHOD FOR ANALYZING AND FORECASTING THE STATE OF MULTIDIMENSIONAL OBJECTS USING A METAHEURISTIC ALGORITHM
    Aqeel Bahr Tarkhan, Oleg Sova, Andrii Lebedynskyi, Yurii Dehtiar, Oleksandr Lytvynenko, et al.
    Eastern European Journal of Enterprise Technologies, 2024
    The object of the study is multidimensional objects. The problem solved in the study is to increase the efficiency of assessing the state of multidimensional objects, regardless of the number of dimensions of object state assessment. The subject of the study is the process of assessing the state of multidimensional objects using an advanced butterfly optimization algorithm (BOA), an advanced genetic algorithm and evolving artificial neural networks. The originality of the study is as follows: – the initial setting of butterfly agents (BA) on the plane of multidimensional objects is carried out taking into account the type of uncertainty using appropriate correction factors for the degree of awareness of nectar source locations (in our case, priority search directions); – adjusting the initial BA velocity allows determining search priority; – the fitness of BA nectar collection sites is determined, which reduces the time for assessing the state of multidimensional objects; – the possibility of global restart of the algorithm, which allows the algorithm to go beyond the current optimum and improve the exploration ability, which reduces the time for assessing the state of multidimensional objects; – the possibility of clarification at the stage of collecting nectar clusters due to ranking nectar sources by the level of stimulus intensity; – improved ability to select the best BA in comparison with traditional selection using an advanced genetic algorithm. The proposed method should be used to solve the problems of assessing the state of multidimensional objects under uncertainty and risks characterized by a high degree of complexity. The method showed a 14–16 % increase in the efficiency of assessing the state of multidimensional objects
  • DEVELOPMENT OF ASSESSMENT AND FORECASTING TECHNIQUES USING FUZZY COGNITIVE MAPS
    Andrii Shyshatskyi, Oleg Sova, Tetiana Stasiuk, Vitalii Andronov, Oleksii Nalapko, et al.
    Technology Audit and Production Reserves, 2023
    Nowadays, no state in the world is able to work on the creation and implementation of artificial intelligence (AI) in isolation from others. AI technologies are used to solve general and highly specialized tasks in various spheres of society. In the process of assessing (identifying) the state of complex objects and objects of management analysis, there is a high degree of a priori uncertainty regarding their state and a small amount of initial data describing them. At the same time, despite the huge amount of information, the degree of non-linearity, illogicality and noisy data is increasing. That is why the issue of improving the efficiency of assessing the condition of components and objects is an important issue. Thus, the objects of analysis were chosen as the research object. The subject of research is the identification and forecasting of the analysis object. In the research, the evaluation and forecasting method was developed using fuzzy cognitive maps. The features of the proposed method are: ‒ taking into account the degree of uncertainty about the object state while calculating the correction factor; ‒ adding a correction factor for data noise as a result of distortion of information about the object state; ‒ reduction of computing costs while assessing the object state; ‒ creation of a multi-level and interconnected description of hierarchical objects; ‒ correction of the description of the object as a result of a change in its current state using a genetic algorithm; ‒ the possibility of performing calculations with source data that are different in nature and units of measurement. It is advisable to implement the proposed method in specialized software, which is used to analyze the state of complex technical systems and while making decisions.
  • THE DEVELOPMENT OF SOLUTION SEARCH METHOD USING IMPROVED JUMPING FROG ALGORITHM
    Ghadeer Al Mamoori, Oleg Sova, Oleksandr Zhuk, Iurii Repilo, Borys Melnyk, et al.
    Eastern European Journal of Enterprise Technologies, 2023
  • DEVELOPMENT OF A SOLUTION SEARCH METHOD USING AN ADVANCED FLYING SQUIRREL ALGORITHM
    Oleg Sova, Oleksandr Zhuk, Oksana Petruchenko, Yurii Artabaiev, Oleksandr Trotsko, et al.
    Eastern European Journal of Enterprise Technologies, 2023
  • DEVELOPMENT OF A METHOD OF COMPLEX ANALYSIS AND MULTIDIMENSIONAL FORECASTING OF THE STATE OF INTELLIGENCE OBJECTS
    Olena Nechyporuk, Oleg Sova, Andrii Shyshatskyi, Serhii Kravchenko, Oleksii Nalapko, et al.
    Eastern European Journal of Enterprise Technologies, 2023
  • DEVELOPMENT OF FORCE DISTRIBUTION METHODOLOGY AND MEANS OF COMMUNICATION FOR THE GROUPING OF TROOPS (FORCES) IN  OPERATIONS
    Oleg Sova, Yurii Zhuravskyi, Andrii Shyshatskyi, Oleksandr Zhuk, Taras Hurskyi, et al.
    Technology Audit and Production Reserves, 2022
  • ANALYSIS OF CONDITIONS AND FACTORS AFFECTING CYBER SECURITY IN THE SPECIAL PURPOSE INFORMATION AND TELECOMMUNICATION SYSTEM
    Oleg Sova
    Technology Audit and Production Reserves, 2022
  • DEVELOPMENT OF METHODOLOGICAL PRINCIPLES OF ROUTING IN NETWORKS OF SPECIAL COMMUNICATION IN THE CONDITIONS OF FIRE DAMAGE AND RADIO ELECTRONIC FLOW
    Oleg Sova
    Technology Audit and Production Reserves, 2022
  • DEVELOPMENT OF METHODOLOGICAL PRINCIPLES OF ROUTING IN NETWORKS OF SPECIAL COMMUNICATION IN CONDITIONS OF FIRE STORM AND RADIO-ELECTRONIC SUPPRESSION
    Oleg Sova, Yurii Zhuravskyi, Yuliia Vakulenko, Andrii Shyshatskyi, Olha Salnikova, et al.
    Eureka Physics and Engineering, 2022
  • DEVELOPMENT OF A METHOD OF MULTI-CRITERIA EVALUATION UNDER UNCERTAINTY
    Oleg Sova, Andrii Shyshatskyi, Oleksii Nalapko, Halyna Marchenko, Oleksandr Trotsko, et al.
    Technology Audit and Production Reserves, 2022
  • IMPROVEMENT OF COMPLEX RESOURCE MANAGEMENT OF SPECIAL-PURPOSE COMMUNICATION SYSTEMS
    Mykhailo Koval, Oleg Sova, Oleksandr Orlov, Andrii Shyshatskyi, Yurii Artabaiev, et al.
    Eastern European Journal of Enterprise Technologies, 2022
  • IMPROVING THE METHOD FOR INCREASING THE EFFICIENCY OF DECISION-MAKING BASED ON BIO-INSPIRED ALGORITHMS
    Mykhailo Koval, Oleg Sova, Andrii Shyshatskyi, Yurii Artabaiev, Nataliia Garashchuk, et al.
    Eastern European Journal of Enterprise Technologies, 2022
  • DEVELOPMENT OF THE METHOD OF INCREASING THE EFFICIENCY OF INFORMATION TRANSFER IN THE SPECIAL PURPOSE NETWORKS
    Oleg Sova, Hryhorii Radzivilov, Andrii Shyshatskyi, Dmytro Shevchenko, Bohdan Molodetskyi, et al.
    Eastern European Journal of Enterprise Technologies, 2022
  • DEVELOPMENT OF A METHOD TO IMPROVE THE RELIABILITY OF ASSESSING THE CONDITION OF THE MONITORING OBJECT IN SPECIALPURPOSE INFORMATION SYSTEMS
    Oleg Sova, Hryhorii Radzivilov, Andrii Shyshatskyi, Pavel Shvets, Valentyna Tkachenko, et al.
    Eastern European Journal of Enterprise Technologies, 2022
  • DEVELOPMENT OF A METHOD FOR INCREASING THE INTERRUPTION PROTECTION OF MULTI-ANTENNA SYSTEMS WITH SPECTRALLY EFFECTIVE SPECIAL PURPOSE SIGNALS UNDER THE INFLUENCE OF DESTABILIZING FACTORS
    Oleg Sova, Andrii Shyshatskyi, Viktor Ostapchuk, Yurii Zhuravskyi, Maksym Rohovets, et al.
    Eastern European Journal of Enterprise Technologies, 2022
  • Modeling of Jamming of the Radio Network with Air Repeater
    Taras Hurskyi, Oleg Sova, Serhiy Boholiy
    2020 IEEE International Conference on Problems of Infocommunications Science and Technology Pic S and T 2020 Proceedings, 2021
  • DEVELOPMENT OF A SIMULATION MODEL FOR A SPECIAL PURPOSE MOBILE RADIO NETWORK CAPABLE OF SELF-ORGANIZATION
    Oleg Sova, Andrii Shyshatskyi, Oleksii Nalapko, Oleksandr Trotsko, Nadiia Protas, et al.
    Technology Audit and Production Reserves, 2021