Компьютерные технологии, управление, радиоэлектроника
Уважаемые коллеги! Приветствуем Вас на нашем сайте! Серия «Компьютерные технологии, управление, радиоэлектроника» была создана в 2001 году и в настоящее время представлена четырьмя выпусками в год. Основной целью редакционная коллегия и редакционный совет серии «Компьютерные технологии, управление, радиоэлектроника» считает пропаганду новых научных достижений и практических разработок по актуальным проблемам компьютерных технологий, управления и радиоэлектроники, способствующих повышению научной и практической квалификации исследователей. Научная концепция издания предполагает публикацию современных достижений в таких областях как: Информатика и компьютерные технологии; Автоматизированные системы управления технологическими процессами; Системы управления летательными аппаратами; Информационно-измерительная техника; Радиотехнические комплексы; Антенная техника; Инфокоммуникационные технологии; Системы автоматизированного управления предприятиями в промышленности. Журнал принимает к публикации оригинальные статьи, результаты экспериментальных исследований, статьи обзорно-аналитического характера, а также статьи в форме кратких сообщений (для молодых ученых, аспирантов и магистрантов). Журнал включен в Перечень ВАК по следующим научным специальностям и соответствующим им отраслям науки: 2.3.1. Системный анализ, управление и обработка информации, статистика (технические науки); 2.3.3. Автоматизация и управление технологическими процессами и производствами (технические науки); 2.3.4. Управление в организационных системах (технические науки). Приглашаем к сотрудничеству всех авторов, разделяющих цели и задачи журнала «Вестник ЮУрГУ. Серия «Компьютерные технологии, управление, радиоэлектроника» Редакционная коллегия
IN MEMORY OF VLADIMIR NIKOLAEVICH BURKOV
Copyright (c) 2025 Computer Technologies, Automatic Control, Radioelectronics
TECHNOLOGY FOR DETERMINING THE OPTIMAL USE OF PROBLEMATIC NATURAL RESOURCE MANAGEMENT OBJECTS BASED ON GEOINFORMATION MANAGEMENT FOR THE PURPOSE OF SPATIAL DEVELOPMENT OF THE TERRITORY
The digital transformation of the agro-industrial sector began in the early 2000s. During this time, many approaches have been developed to monitor the condition of agricultural land, automate crop care, high-precision fertilization, monitor animal health, and optimize the operation of agricultural machinery. Nevertheless, the inventory of agricultural land has not been carried out for more than 30 years and, therefore, it is relevant to develop methods for assessing problematic environmental management facilities in order to determine the directions of their further application. The main goal of introducing precision farming technologies is to change the decision-making process and, as a result, to significantly improve the management efficiency of agricultural enterprises, reduce environmental pollution, increase agricultural producers' incomes and improve product quality. Aim. To develop a universal intelligent module for the UralGIS-Agro information system, which would allow detecting problematic environmental management objects based on satellite images. Materials and methods. Methods of analyzing images obtained using remote sensing of the Earth (satellite images) were used to detect problematic environmental management objects. In particular, the developed methodology makes it possible to analyze the indices (vegetation, water) and, based on the values obtained, a decision is made on the condition of the facility. Results. The resulting module is universal. Depending on the input data about the contours of the objects and the calculated indexes, it allows you to get an analysis of the object in the required context. The economic efficiency of the developed system is calculated. Conclusion. Based on the results of the module, problematic environmental management facilities in the Chelyabinsk region were identified, the benefits for the region were determined if the discovered facilities were transferred to other owners, as well as the possible costs of restoring these lands as agricultural. The intelligent module considered in this article is part of the technology for determining the optimal use of problematic environmental management facilities, it allows us to further solve the problem of balanced development of the territory based on geospatial analysis and artificial intelligence algorithms.
BRIDGE “MAINLAND – SAKHALIN”: PROBLEMS OF CONSTRUCTION AT THE PRESENT STAGE
Purpose of the study. Due to the rapid escalation of the conflict between Russia and the West, as a result of which Russia is naturally moving closer to the East. In this regard, an urgent problem is to improve the transport accessibility of remote areas, such as Sakhalin, which is the largest island in Russia and has signif-icant natural resources. In this regard, Russian President Vladimir Putin supported the initiative to build a bridge connecting Sakhalin with the mainland, believing that this would help accele¬rate the development of the region. Materials and methods. In the course of the study, a retrospective of the large-scale investment railway project (KIP-railway) “mainland – Sakhalin” was given, and the main elements of the transport in-terchange were highlighted. The analysis showed that the lack of a direct bridge connection with the main-land significantly hinders the development of the economy of the “eastern vector”. Similar examples of successful development of regions with bridges, such as Crimea or Kamchatka, indicate that the construc-tion of a bridge between Sakhalin and the mainland can stimulate economic growth, improve the invest-ment climate and improve the quality of life of the local population. Results. The customer faces a difficult choice in terms of the coalition of elements of the transport interchange (hereinafter referred to as pro-jects) “mainland – Sakhalin”. To reduce uncertainty, a special software product ASPRER was used in this article. With the help of the program, expert rankings were obtained on an ordinal scale in numerical for-mat, in the form of coefficients of relative importance (COV). To combine projects into va¬rious coalitions using the Shapley method, sustainability and reliability of project implementation are achieved. The calculations performed demonstrate the work of a set of tools necessary for the customer to ensure transparency and validity of their own decisions. Conclusion. The tools offered to the customer also allow for the pre-investment stage of the KIP-railway assessment to structure the existing uncertainty and avoid cata-strophic errors at the pre-investment stage of project evaluation.
SYNTHESIS OF COMPETENCE CENTERS OF THE RUSSIAN FEDERATION EMERCOM IN THE FIELD OF FIRE SAFETY
The article considers the issues of forming a more effective structure of the Ministry of Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters in planning and implementing measures to ensure fire safety at economic facilities by creating knowledge-intensive organizational structures capable of meeting the interests of the state, specialists in the subject area and business communities in choosing highly professional alternatives to the works and services offered on the market. Objective. The main objective of the work is to build a mechanism that facilitates the solution of the tasks set before the control and supervisory bodies of the emergency department to reduce potential threats and damage from possible fires at facilities for various purposes. To develop this mechanism, the authors propose to consider the possibility of synthesizing a specialized structure in the governing bodies and territorial divisions of the federal state fire supervision – competence centers of the Ministry of Emergency Situations of Russia in the field of ensuring fire safety. Methods. The study presents a systematic approach to the implementation of the principles of organizational design of structural divisions of territorial bodies of the Ministry of Emergency Situations of Russia, which allows creating new high-quality mechanisms for ensuring fire safety of capital construction projects, taking into account the provision of a set of variable solutions to the copyright holders of these objects on the principles of customer focus and consistency. Results. The analysis of the need to implement competence centers of the Ministry of Emergency Situations of Russia, a list of tasks facing them and the main functions of the proposed structures is carried out. A mathematical description, a simplified algorithm for the interaction of elements of the decision-making support system in matters of ensuring fire safety using competence centers and the architecture of the proposed information software product are also presented. The authors propose an approach to improving the process of forming the organizational structure of these divisions by modernizing management tools for ensuring fire safety, as well as project management by forming competence centers of the Ministry of Emergency Situations of Russia in the field of fire protection of economic entities. Conclusion. The synthesis of competence centers of the Ministry of Emergency Situations of Russia in the field of ensuring fire safety can be an important step towards forming a more effective system of ensuring fire safety in specific regions and in the Russian Federation as a whole.
In this work basic approaches to project management of IT of a profile in a foreground mode are considered, especially when entering adjustments into structure of projects which undoubtedly has the specific features. The main difference from a stage of forming of the program of project management is that the exception of it can lead to the additional expenses connected with the termination of already begun works, therefore, risks of failure to follow the specified projects increase at the scheduled time. Compensations to performers, penalties for cancellation of contracts and other similar losses belong to such expenses, for example. Task analysis of operational management of the program and a portfolio of IT of projects taking into account these additional expenses is presented in many works. However, for a solution of similar tasks application of any only method is not always possible that sets a task of development of an integrated approach to risk assessment of IT of projects for the choice of the least risky that demands researches in the field of mechanisms of complex estimation. The research objective consists in forming of expert system of support of decision-making at risk assessment of IT of projects taking into account contradictions of knowledge of experts and forming of a compromise in problems of complex estimation and paired comparisons. Research methods. Are applied by projects taking into account risks to a solution of a problem of operational planning of IT: the method of network programming and a method based on the table of admissible solutions. At risk assessment the qualimetrical scale creating three groups forms: low risks, average risks and high risks. At the same time the system of points is appropriated to each group of risks that allows experts to create rather sure estimates. Results. The offered effective algorithm of receiving expert estimates allowed to simplify the procedure of creation of tables of admissible solutions. If the table size (number of the considered solutions) exceeds the set restriction, “compression” of the table to the required size by “pasting” of solutions is made. Pasting of solutions happens in such a way that any admissible solution is not lost (however, inadmissible solutions can appear). As a result we receive upper assessment for an initial problem of risk assessment of IT of projects. Thus, thanks to it is applicable methods of network programming it is possible to exclude the probability of receiving incorrect estimates and uncoordinated opinions of experts at selection of IT of projects in total portfolio of the company of the developer. Conclusion. To receive from experts exhaustive and not contradictory results which will be based on simple and clear actions it is necessary to apply the offered approach to a solution of complex estimation of risks of IT of projects. The first way of accounting of risks (restriction for financing of projects with high and average risks) is effective if value grows with growth of n is polynomial. The second and third ways generally lead to the exponential growth of complexity. However, if the number of projects with high and average risks is limited on top to some number K (which is not depending from n), then both of these ways are effective.
MODEL OF INCREMENTAL DATA MIGRATION IN ERP IMPLEMENTATION PROJECTS
Data migration plays a crucial role in the implementation of ERP. Migration scenarios can be quite complex and prolonged, requiring significant resources and a high level of expertise from organization personnel. Inadequate assessment of available resources may lead to a substantial increase in costs and disruption of the planned timelines for the launch of the ERP system. However, the complexity of migration scenarios is often underestimated. The majority of existing research primarily focuses on the technical aspects of data migration, while conceptual elements, such as the relationship between data migration and business processes, remain insufficiently explored. The aim of the study. This article aims to develop a data migration model that considers the interaction between business processes and data during the ERP system implementation, with the goal of enhancing the effectiveness of migration projects and minimizing risks. Materials and methods. The study employs algorithmic modeling techniques and Business Process Model and Notation (BPMN) to create an incremental data migration strategy. Results. The outcome of the research is a data migration model that reflects the interrelationship between data and business proces¬ses. This model includes the definition of migration states and transitions between them, necessary parameters and variables that reflect the involvement of stakeholders at various stages of migration, and the execution of relevant tasks to ensure the data migration process. The model also establishes key performance indicators that enable more accurate assessment of risks and resources required for the successful completion of migration. Conclusion. The proposed model can serve as a foundation for effective planning of data migration within the framework of ERP system implementation, which is a requisite condition for achieving business objectives and enhancing operational efficiency in organizations.
DECOMPOSITION OF PRICE-FORMING FACTORS BASED ON STATISTICAL ANALYSIS OF EXPERT ASSESSMENTS OF THEIR SIGNIFICANCE
This study addresses the problem of mass appraisal of market value. In the context of deve¬loped markets, numerous studies have demonstrated the effectiveness of distinguishing, among all characteristics describing the object of valuation, those factors that are suitable for solving the classification task, while the remaining pricing factors are used to solve the regression task – namely, estimating the most probable price. Despite the demonstrated efficiency of this multi-model approach, there is no widely accepted methodology for separating descriptive features into classification and pricing categories. The aim of this study is to scientifically substantiate the effectiveness of decomposing features into classification and pricing groups through statistical analysis of expert assessments of feature importance. The hypothesis tested in this study suggests that features with high importance (as determined by mean, median, or mode) and high dispersion (i.e., a high coefficient of variation) should be treated as classification factors, whereas features with high importance and low dispersion should be treated as price-forming factors. Materials and Methods. Passenger vehicles are selected as the objects of valuation. The vehicle database used for deve-loping mass appraisal models contained three million records. To assess the influence of various vehicle parameters on price, a survey was conducted among 18 experts – professional market participants. The mean, median, and mode of expert assessments were used to rank the importance of the factors, while variance and coefficient of variation were applied for feature decomposition. A variety of mass appraisal models were developed using both classical regression methods and machine learning techniques (gradient boos¬ting, random forest, and artificial neural networks), with and without the separation of pricing factors. Results. The models that incorporated the separation of pricing factors demonstrated an average increase of 5–7 % in the coefficient of determination (R²) compared to models that used all features as a single set. Conclusion. The proposed approach to mass appraisal can be adapted to other types of valuation objects. The method based on statistical analysis of expert evaluations of feature importance is of a universal nature. This defines its practical significance, as appraisers and analysts in various domains often face substantial resource demands – time, computational, human, and financial – for constructing reliable mass appraisal models of market value.
HYBRID METHOD OF CLASSIFICATION OF TEXT DATA WITH SPECIALIZED TERMINOLOGY
In the context of exponential growth of text information, especially in domain-specific areas (technical, medical, legal), the task of automatic classification of texts saturated with highly specialized terminology is of critical importance. Existing approaches, including transformer models (BERT), often demonstrate a decrease in accuracy when working with rare or domain-specific vocabulary due to training on common corpora. The aim of the study is to develop a hybrid method Combined Neural BERT (CNB), which provides maximum classification accuracy (100 %) for texts with specialized terminology due to the synergistic combination of the advantages of contextual language models, lexical-statistical methods, and visualization tools. Materials and methods. The proposed CNB method integrates three key components: 1) BERT (or its derivatives) for generating deep contextual embeddings that take into account semantics and word order; 2) fully connected neural networks (FCNN) acting as a classifier based on BERT features and/or processing lexical-statistical features; 3) the Word Cloud method and TF-IDF for extracting and visualizing key domain terms, forming a feature dictionary and improving interpretability. The architecture of the method includes the following stages: text preprocessing (normalization, cleaning), parallel feature extraction (BERT contextual embeddings + TF-IDF vectors), merging feature spaces, classification using FCNN, interactive tuning based on the Word Cloud analysis. Results. The hybrid CNB approach was tested on a real corpus of 10,000 requests from residents of the Chelyabinsk region (7 thematic categories) using 70 key terms and 150 stop words. The method demonstrated 100 % classification accuracy after three training iterations (total time is 90 minutes). Key benefits: Higher accuracy due to compensation of BERT's weaknesses in specialized domains with lexical-statistical features; Improved interpretability due to visualization of key terms with the “Word Cloud”; Efficiency of processing large volumes of specialized texts. Conclusion. The developed hybrid CNB method has proven its exceptional efficiency for classifying texts with highly specialized terminology. It is a powerful tool for analyzing domain-specific text arrays (legal documents, technical documentation, medical reports, etc.) in the context of constantly growing data volu¬mes. Prospects include adapting the method to other domains and optimizing computational efficiency.
ONTOLOGY-BASED EQUIPMENT RESOURCE CONTROL IN KNOWLEDGE-INTENSIVE MANUFACTURING
Modern knowledge-intensive manufacturing requires high precision, reliability, and efficiency of equipment operation. The failure of critical components can lead to significant financial losses, disruption of technological processes, and safety risks. In this context, equipment management and residual life prediction become key tasks to ensure uninterrupted production. This study analyzes the influence of technological parameters and steel chemical composition on the residual life of continuous casting machine molds. A comprehensive ontological model integrating data on steel temperature, mechanical loads, alloying elements, and equipment geometric characteristics has been developed. Objective: to design an ontological model for semantic integration of heterogeneous data and improving equipment residual life prediction accuracy using a hybrid approach combining ontological engineering and machine learning methods. Materials and methods. An OWL ontology was developed, including classes such as “Mold,” “Chemical Composition,” and “Technological Parameters.” SPARQL queries were implemented to identify dependencies between operational parameters and mold residual life. Machine learning methods were integrated for prediction and anomaly detection. Results. Key influencing factors were identified: steel temperature, copper content, and billet geometry. A prediction accuracy of R² = 0.85 was achieved, surpassing traditional statistical methods. Logical inference rules were developed for automatic detection of critical equipment conditions. Conclusion. The study demonstrated the effectiveness of a comprehensive approach to predicting the residual life of continuous casting machine molds, combining analysis of technological parameters, steel chemical composition, and equipment geometry. The integration of machine learning and ontological engineering into high-tech equipment management enables a shift from reactive to predictive maintenance, reducing costs and improving reliability. This is particularly crucial in industries where downtime costs are extremely high, and safety and precision requirements are critical. Further development of these technologies, including integration with digital twins and cognitive systems, opens new opportunities for Industry 4.0 and smart manufacturing.
MATHEMATICAL SOFTWARE APPLICATION FOR AN ANALYTICAL GEOMETRY PROBLEM WITH A PARAMETER SOLVING AND VISUALIZATION
In this issue we study the possibility of mathematical software usage for analytical geometry with parameters problem solving. A review of Russian and foreign sources has shown that, despite the variety of mathematical software applications, they are rarely used to solve problems with parameters. The purpose of the study was to test the possibility of a mathematical package usage to solve problems with parameters, which will allow to avoid arithmetic and other errors and to obtain a tool for generating different variants of the same problem and a template for students’ solutions checking. Materials and methods. We used Mathcad 15.0 environment for the straight line and an ellipse with a variable symmetry center ordinate relative position determination. First analytical solution of the relative position of a straight line and a second-order curve with a parameter problem is based on the number of curves’ common points and their coordinates functional dependence on the parameter analysis. Second one is based on the point of contact coordinates determination using the equality of the straight line angular coefficients and curve tangent at the point of contact. Results. In this study it was established that Mathcad allows to implement both analytical methods and directly find the expressions for the coordinates of the depending on the parameter by solving a system of nonlinear equations and then to exam them for the set of real numbers belonging. Conclusion. Our research ascertains that Mathcad can be implemented for visualization and various solutions of analytical geometry with a parameter problem. Mathcad solution can be used to generate a set of different variants of the same problem with a rational number results, to verify students’ problem solutions, and also as an example of correct solution.
APPLICATION OF NEURAL NETWORK ALGORITHMS INFORMATION PROCESSING IN AUTONOMOUS VIDEO MONITORING SYSTEMS
The article is devoted to the problem of processing video information using neural networks in autonomous systems with limited computing resources. The purpose of the study. The purpose of the ar¬ticle is to study algorithms for processing video information in autonomous systems with limited computing resources based on two-stage data processing. At the first stage, the contours of the observed objects are determined using traditional methods of identifying key features. The second stage involves processing using neural network algorithms aimed at classifying and recognizing objects. Due to the primary processing of the video stream, the amount of information processed by the neural network is significantly reduced. Materials and methods. The article offers a variant of the algorithm for primary processing of video information based on methods for determining the contours of objects. Boundary allocation methods based on spatial filtering can be applied to both stationary and mobile objects. Secondary processing is based on the use of a convolutional neural network, the coefficients of which were quantized to reduce the computational load. To train the neural network, two datasets were generated for training, navigation, and testing. The first dataset consisted of initial images with an object, the second contained an ideal contour of objects (masks). A comparison of two neural networks trained on the source images and on contour masks of the images is carried out. The features of the implementation of neural networks on FPGAs are considered and a block diagram of the calculations is proposed. The possibility of iterative calculations with repeated use of computing resources at each iteration (neural network layer) is shown. Results. The results of preliminary studies on neural network training and quantization of its coefficients are presented, and the specifics of hardware implementation of neural networks based on programmable logic integrated circuits are considered. Conclusion. The two-stage approach to video information processing demonstrates high efficiency in autonomous systems where there are limitations on energy consumption and computing resources. The article may be useful to developers of autonomous video monitoring systems, detection and tracking of ground-based and air-based facilities.
MULTICRITERIA TASK OF FORMING GENERATIONS OF NEW TECHNOLOGY
The purpose of the study. It is noted that the priority direction of economic development is innovation, and this implies the organization of work on the formation of generations of new technology. This circumstance is caused by a number of factors. It is shown that in the course of solving these problems, the most promising methods are the multi-criteria description of the problem. Hence, there is a need to reduce the methods of multi-criteria optimization in relation to the tasks formation of new generations of technology. The complexity of the process of developing innovative solutions that ensure accounting is noted technological, economic and environmental factors. A formal statement of the problem of choosing technologies that maximize revenue within the allocated budget with a minimum number of selected solutions is given. Materials and methods. Methods for solving multi-criteria problems are considered, inclu¬ding the classical method of branches and boundaries, dynamic programming, greedy and heuristic algorithms, hierarchy analysis, the assignment method, evolutionary algorithms and the Pareto method. Special attention is paid to the formation of a Pareto-optimal set, which makes it possible to reduce the number of alternatives by eliminating inefficient solutions. It demonstrates how discretization of the cost interval and solving a series of integer programming problems generate points on the Pareto curve. Results. The practical significance of the research is explained by the needs in the course of construction project management, where optimization reduces costs, and antimonopoly regulation through the analysis of graphs of market interactions. Recently, there has been widespread use of PLM systems and artificial intelligence in improving the efficiency of such developments. At the same time, the problem of creating environmentally friendly technologies should not be left out. Conclusion. The need to integrate mathematical models with modern management tools is emphasized in order to minimize subjectivity in decision-making. The use of multi-criteria models, machine learning methods, and adaptation of approaches to non-Markov processes is considered a promising area. It is shown how the transition from a multi-criteria task to a sequence of traditional optimization tasks is possible. It is emphasized that in this case, a Pareto-optimal set of solutions to the problem under consideration is constructed.
DIGITAL TWIN-BASED MANAGEMENT MODEL FOR HIGH-TECH PRODUCTION
A management model for high-tech production based on digital twin technology is presented, combining the architecture of a data lake and the principles of ontological engineering and an agent-based service approach. The study examines the problems of managing complex production environments in the context of Industry 4.0, and suggests a hybrid approach combining the principles of a “smart factory” with lean manufacturing methodologies. The model includes a multi-level architecture covering strategic, tactical and operational levels, supported by an agent-service structure for system integration. The aim of the work is to develop an integrated management model for high-tech production based on the integration of digital twin technology, an ontological approach, and an agent-service architecture using a data lake. Methods. The research methodology uses a systematic approach to data management using data lake and electronic passports, and fuzzy ontologies to formalize knowledge. Results. The implementation is demonstrated on the example of multiscale modeling of chemical materials and compounds, where the effectiveness of the model is quantified. The results indicate a significant increase in productivity, especially in data retrieval operations, as structured search protocols demonstrate higher efficiency compared to traditional approaches. Conclusion. The results show that integration of digital twins with ontological structures and architectures of agency services provides enhanced operational control and decision-making capabilities in high-tech production environments. The practical application of the model demonstrates its scalability and adaptability in various industries, contributing to both theoretical understanding and practical implementation of advanced production systems. This research develops the field of high-tech production management by providing a structured framework for the digital transformation of production operations.
A METHODOLOGICAL APPROACH TO THE MANAGEMENT OF GENERAL EDUCATION INSTITUTIONS THROUGH MATERIAL RESOURCE PROVISION
This study focuses on a methodological approach that views the school as a holistic entity interacting simultaneously with multiple agents, as well as on the pressing issue of how material resources influence the management of the educational process in Russian schools. The article presents several models of interaction between schools and suppliers, tested through interviews with school principals and supplier company representatives. Aim. The aim is to сonsider the school as an integral object and to determine the impact of the material base on the educational process in Russian schools. Materials and methods. The approach based on the formation of the goal tree is widely used to solve them. To identify the fundamental management mechanisms used, we applied the decomposition of goals, which showed the most significant impact of the cost-effect mechanism on several keys related to equipment goals of schools. Furthermore, we carried out a quantitative analysis of the results in this study, implying a rating of spending directions within the cost-effect mechanism framework. To highlight the essential equipment cate¬gories, we calculated the correlations between the number of students with exam scores above 251/300 points of a state exam and the cost of this type of equipment. Results. As it turned out, laboratory and digital equipment have the most significant correlations. Purchases of educational literature have a more negligible effect. School procurement of equipment is described by three key control mechanisms: supply chain optimization, incentive, and cost-effect mechanisms. Conclusion. This article discusses the issues of determining the effectiveness of school procurement indicators based on the decomposition of the goals of secondary school principals, and describes the procurement management mechanisms for various types of equipment that affect vital results. Data on the potential impact of purchases of various types of school equipment on educational outcomes has been obtained and the cost-effect mechanism applied to schools has been described.
PROBLEMATICS OF AUTHENTICITY VERIFICATION, COPYRIGHT AND DIGITAL DATA INTEGRITY
Nowadays, the problem of ensuring the security of digital data is becoming more urgent than ever. Consumers of digital data or information are almost all people in most spheres of life. Secure data in the context of research is data whose origin is reliable, its integrity is intact, and copyrights are respected. Digital data protection methods are being improved every year in an effort to prevent information theft and protect people from false or deliberately false information. However, with all its diversity and technological maturity, modern approaches to verifying the authenticity, copyright and integrity of multimedia and tools based on them cannot always fully protect consumers of information from modern cyber threats. Introduction of something new does not always eliminate the conceptual problems of what was before. New approaches, tools, and standards often introduce new vulnerabilities that are used by attackers. Research goal. To analyze modern methods and technologies for verifying authenticity, copyright and integrity of multimedia data, as well as to propose an integrated approach that can help to solve the identified problems. Materials and methods. Retrospective method is used to analyze the historical development of data protection technologies, cryptographic approaches, as well as modern solutions based on blockchain and machine learning. Results. The analysis showed that traditional cryptographic methods, despite their effectiveness in ensuring data integrity, face limitations in distributed systems due to the lack of uniform standards and the complexity of scaling. Conclusion. Despite the variety of existing technologies for verifying the authorship, integrity, and authenticity of digital data in general and multimedia in particular, today the problems of lack of standardization and fragmentation of solutions remain among key challenges in the area of making digital data secure in its entirety.
ДАТЧИК УГЛА ПОВОРОТА ДЛЯ КОНТРОЛЯ ПОЛОЖЕНИЯ ИСПОЛНИТЕЛЬНЫХ УСТРОЙСТВ
Надежность работы исполнительных устройств определяется критериями предельных состояний, которые оцениваются различными типами датчиков. Надёжность датчиков зависит от их конструктивных свойств, особенностей технологического обеспечения их качества в процессе производства. Угловое положение поворотных звеньев исполнительных механизмов определяется различными типами датчиков, в том числе датчиками угла поворота. Рассматривается датчик бесконтактного типа. Работа датчика основана на принципе измерения Холла, что обеспечивает его конструктивную простоту, надежность и длительный срок службы. Точностные характеристики датчика определяются погрешностями изготовления его отдельных частей. Цель исследования: разработать модель погрешности датчика в зависимости от неточностей изготовления постоянного магнита, входящего в состав его первичного измерительного преобразователя. Материалы и методы. В качестве прототипа выбран датчик угла поворота производства СКБ «Индукция», в процессе производства которого обнаружены отклонения его технических характеристик, вызванные дефектами постоянных магнитов. В работе использованы методы теоретической механики, расчета электрических и магнитных цепей, численного моделирования. Расчеты проведены для постоянного магнита цилиндрической формы с радиальной намагниченностью, при этом вектор намагниченности смещен в радиальном направлении. Для выполнения расчетов погрешностей использованы схемы расположения дефектных магнитов относительно вектора намагниченности внешнего поля, создаваемого дополнительными магнитами. Соосное расположение дополнительных магнитов обеспечивается путем расположения их в соосных цилиндрических направляющих. Результаты. Приводятся аналитические зависимости, связывающие смещение диполя магнита относительно его геометрического центра с погрешностью определения угла поворота. Погрешности датчика представлены на эскизах первичного измерительного преобразователя в различных положениях магнита относительно элементов Холла в первичном преобразователе. Заключение. Результаты исследования могут быть использованы в технологической оснастке, позволяющей дать количественную оценку величины радиального смещения магнитного диполя относительно геометрического центра магнита. Практическая значимость результатов состоит в отбраковке постоянных магнитов на этапе входного контроля допустимого смещения магнитного диполя относительно его геометрического центра.
Instrument Engineering, Metrology and Information and Measuring Devices and Systems
DETECTION OF ROTOR FAULTS IN INDUCTION MOTOR BY HIGHER CURRENT HARMONICS USING THE MATRIX PENCIL METHOD
Broken rotor bars in the squirrel-cage winding of an induction motor are one of the causes of premature failure in industrial equipment. A broken rotor bar leads to motor overheating, increased vibration, and reduced operational efficiency. Conventional rotor fault diagnostic methods, based on detecting fault-related frequency components near the supply harmonic in current spectra, often prove insufficiently accurate due to various masking effects, such as current signal noise, rotor design peculiarities, and changing operating conditions. The aim of the study: to apply the Matrix Pencil Method (MPM) to motor current signals to extract the amplitudes and frequencies of higher-order rotor fault harmonics near the 5th and 7th supply harmonics. These higher-order rotor fault harmonics are less susceptible to masking effects and provide more reliable indicators of rotor faults compared to components near the fundamental supply frequency. Materials and methods. The Matrix Pencil Method offers superior spectral resolution and computational efficiency compared to Fourier transform-based spectral analysis techniques. Additional signal processing, including filtering and demodulation based on squared current summation, enhances the accuracy and reliability of detecting higher-order rotor fault harmonics. Results. The analysis of real motor current signals with rotor faults demonstrated that as motor load increases and the fault progresses, the amplitudes of rotor fault harmonics also rise. Thus, these parameters can serve as effective diagnostic indicators. The Matrix Pencil Method accurately determines the frequencies and amplitudes of rotor fault harmonics even at a low sampling rate of 100 Hz and a signal length of 200 samples. Conclusion. The Matrix Pencil Method is an effective tool for monitoring the condition of induction motors, as it tracks both the frequency shifts and amplitude growth of fault-related harmonics as the defect develops. Therefore, this method can be practically applied for early fault detection in induction motors, helping to prevent critical failures and unplanned downtime.
NEURAL NETWORK OPTIMIZATION OF AREAS OF EXISTENCE OF THE SLIDING MODE ON THE BASIS OF QUALITATIVE ANALYSIS OF PHASE SPACE PROJECTIONS
The paper proposes a method for neural network optimization of the regions of existence of a sliding mode in the projections of the phase space of a control object for the purpose of subsequent synthesis of control systems with sliding modes. Expanding the regions of existence of a sliding mode provides greater freedom in choosing sliding surfaces, including nonlinear ones, and allows us to expect an improvement in the quality of control. The purpose of the study is to determine the applicability of modern machine learning methods, in particular neural networks and genetic algorithms, in problems of optimizing the regions of existence of a sliding mode using the example of a 4th order nonlinear system. Materials and Methods. To solve the problem, numerical methods of machine learning of neural networks and stochastic directed search, in particular, genetic algorithms, are used. A method for analyzing particular two-dimensional projections of the phase space of a multidimensional system is also used. Results. A structural classification of phase space projections with neural network optimization of the regions of existence of a sliding mode is proposed to ensure automated synthesis of control algorithms. The paper considers the features of phase space projections of multidimensional systems using a fourth-order pulse converter as an example. It proposes a method for constructing switching lines for a sliding mode based on phase space projections, which allows classifying projections in terms of their suitability for organizing control in a sli-ding mode. The sliding mode existence regions are maximized using a stochastic genetic algorithm and a neural network in the form of a multilayer perceptron. The network is implemented using the TensorFlow library for constructing and training neural networks. The Adam optimizer is used to update the model. It is shown that optimization using a genetic algorithm and a neural network allows for a significant increase in the potential for selecting control algorithms by expanding the sliding mode existence regions in phase space projections. Conclusion. The results of the application of the genetic algorithm and training of a multilayer neural network demonstrate that the proposed method expands the scope of application of phase space projections in problems of synthesis of control of multidimensional nonlinear systems and opens up new possibilities for increasing the efficiency of control in sliding modes.
WRITING OUT INERTIAL MATRICES OF HINGED TREE-SHAPED SYSTEMS
The goal is to develop a formalism (a sequence of formal actions) for deriving formulas for calculating the Elements of the Matrix of Inertial Coefficients (EMIC) of Tree-Like Systems with Open Branches (TSOB), whose bodies form hinges between each other, i. e., rotational kinematic pairs of the fifth class. Research methods relate to mechanics of systems of bodies, system analysis, and robotics. The results of the study contain a new formalism for automatically deriving EMIC calculation formulas, i. e., coef¬ficients in the products of relative angular velocities of bodies in the expression of kinetic energy of TSOB. EMIC formulas include constant structural, geometric, and inertial parameters of the considered TSOB. These formulas are represented as quadratic forms with respect to the direction cosines between the axes of coordinate systems rigidly connected to the bodies. The effectiveness of the formalism is demonstrated by examples of manual derivation of EMICs for a three-link angular Manipulator Robot (MR) in the vertical plane, two-armed MRs with five and seven degrees of freedom on the plane and in space. For an MR in space, the problem of synthesizing its parameters, for which EMICs do not depend on body rotation angles, has been solved. Conclusion. The proposed formalism can be used to derive EMICs for typical angular MRs, as well as walking devices in single-support phase of walking or flight, e. g., to derive dynamic equations based on them in the form of Lagrange's second-order equation. Applying known methods of constraint accounting expands the use of EMICs to TSDB, i. e., to TSOBs with end-body constraints, as well as to TSDBs with variable structure, which is relevant for deriving dynamic equations for walking machines and apparatuses in different phases of motion.
STUDY OF THE POSSIBILITY OF TRAFFIC LIGHT CONTROL MODELING OF A COMPLEX INTERSECTION BY AnyLogic
Insufficient capacity of the road network is a problem in most cities. This problem can be partially solved by optimizing the operation of the traffic light. Since selecting traffic light settings in real time can lead to a deterioration in the traffic situation, it is advisable to pre-configure the model and work out various traffic light operating modes on it, and select the optimal ones. The purpose of the study was to simulate changes in the average number of cars in a queue before a traffic light and the average travel time of an intersection. To achieve this goal, the following tasks are formulated: creating a model of a road section with real flows at the entrances; determining the average number of cars in a queue under different traffic light operating modes; creating an experiment to find the average time of a left turn with and without the introduction of a specialized left-turn phase of the traffic light. Materials and methods. To solve the tasks set, the method of using the AnyLogic environment for analyzing a traffic section has been tested, and the possibility of using simulation modeling to identify the dependence of the intersection's capacity on the operating mode of the traffic light has been shown. Results. In the course of the research, a model of the existing intersection was created and the dependence of the number of cars in the queue in front of the forbidding traffic light signal on the duration of its full cycle was considered. To conduct the experiment, the existing 84-second traffic light cycle was changed to 30 seconds, one, two, three, and five minutes. To visualize the obtained dependencies, a graph is constructed that reflects the number of cars in a traffic jam under different traffic light operating modes. The created model is also used to determine the dependence of the travel time of an intersection at a left turn on the number of turning cars and the number of cars in the opposite direction. Traffic light options with and without an additional left signal are considered. The results are presented in a table and graphically. Conclusion. The study showed that with a small amount of oncoming traffic, the introduction of a specialized left-turn phase of the traffic light increases the travel time of the intersection, but with an increase in oncoming traffic, the situation changes to the opposite.
COMPARATIVE ANALYSIS OF RAG METHODS FOR BUILDING RUSSIAN-SPEAKING INTELLIGENT SERVICES
The paper discusses one of the currently most popular approaches to building various types of intelligent assistants and query-response systems based on large language models (LLMs), based on in-context learning or retrieval augmented generation (RAG). The recent proliferation of publications on this topic is primarily English-oriented and utilizes leading-quality models such as GPT-4o and their developments. At the same time, evaluations of RAG context search methods for Russian language tasks are practically absent, which makes it an urgent task to conduct research aimed at adapting and evaluating these methods for the Russian language. Aim. To study the effectiveness of different retrieval augmented generation (RAG) approaches for Russian-language tasks, given that most studies in this area are English-oriented and use leading models such as GPT-4. Materials and Methods. The paper reviews three basic approaches to RAG construction: naive RAG, HyDE, and a probabilistic approach based on the BM25 function. Particular attention is paid to assessing the quality of these methods in terms of the mean average precision (mAP) metric for the three knowledge domains. Combined RAG methods such as SelfRAG were not used to obtain separate evaluations of each approach. Russian language text corpora were selected for the experiments for the knowledge domains: oil and gas industry and jurisprudence. Results. The conducted study allowed us to obtain quality scores for each of the considered methods. The results agree well with the data of other studies, but are inferior to the known RAGs in English. Conclusion. The obtained results can be used as baseline evaluations and as a basis for making decisions on selecting optimal RAG architectures for Russian-language tasks. Further research will be aimed at integrating combined methods and adapting models to improve the quality of Russian language generation.
ANALYSIS OF THE EFFICIENCY OF REGIONAL INNOVATION PROJECTS
The purpose of the study. The purpose of the article is to analyze the role of innovative investments in the qualitative development of regions. At the same time, the problems of the complex influence of environmental, social, economic and scientific-technical factors on regional innovative projects should be disclosed, and direct and indirect costs of project management associated with these factors should be studied. The subject is management relations that arise during innovative design in the regional management system. Materials and methods. The methodological basis of the work is the use of system analysis, statistical analysis methods, mathematical modeling. The article reveals the content of the effect of a regional innovative project. The traditional model for assessing a regional innovative project is consi-dered, and the disadvantages of the model are highlighted. The work also discloses the UNIDO standard. It is noted that in order to assess the effectiveness of a regional innovative project, it is necessary to analyze the role and state of the entity, the economic state of the region and directly the social and environmental consequences that are expected when implementing the project. The assessment of capital-forming investment projects is also considered. Results. The result of the work is an economic and mathematical model for assessing and selecting a regional innovative project, taking into account economic, social and environmental factors. To solve this multi-criteria problem with contradictory criteria, various methods and algorithms of multi-criteria optimization are considered, including the method of convolution of criteria, obtaining one, sometimes quite complex formula, methods for obtaining a Pareto-optimal solution, the Saaty hierarchy method. Quite significant shortcomings inherent in these methods are noted. The most effective method for this model is the method of successive concessions. The scope of application of the results is a comprehensive assessment of the innovation project in order to select the most effective option that fully takes into account the main aspects of the region's life (economic, social and environmental). Conclusion. The use of the complex multi-criteria economic and mathematical model for choosing a regional innovation project given in the article, taking into account economic, social and environmental factors, will increase the level of adequacy of decisions made by regional authorities in terms of choosing effective projects.
ANALYZING APPROACHES, METHODS, AND TECHNOLOGIES FOR IMPROVING THE EFFICIENCY OF INDUSTRIAL ENTERPRISES PRODUCING AND USING BIMETAL SHEET MATERIALS
The problems of increasing the efficiency of work of industrial enterprises and organisations have become more and more important in recent years. The necessity of solving such a problem becomes real both for industrial enterprises and organisations as a whole, and for enterprises connected with production and operation of technological equipment made of bimetallic sheet materials. Aim. Taking into account a large number of researches and developments aimed at increasing the efficiency of functioning of industrial enterprises, the authors of this article aim to present the most significant and successful studies devoted to solving these problems. Materials and methods. The analysis of management approaches, means, technologies and mechanisms for improving the efficiency of industrial enterprises engaged in the production of products and operation of structures from bimetallic sheet materials is based on a significant amount of scientific materials presented in scientific and technical literature. Results. A set of the most significant measures for improving the work of industrial enterprises and organisations is presented, and emphasis is placed on those proposals that will achieve the most significant results for enterprises producing and using bimetallic sheet materials. Conclusion. The article shows that the increase of efficiency of industrial enterprises functioning, which activity is connected with the production or use of products and constructions from multilayer bimetallic materials, should be carried out on the basis of actual approaches, means and mechanisms, including the creation of methods and algorithms of preparation and decision-making by mana¬gers of enterprises in the main direction of their activities, the development of modern information mana¬gement systems, as well as the development of new, promising solutions for the development of new technologies and technologies in the field of bimetallic materials.
IMPROVING THE EFFICIENCY OF MANAGING HIGHER EDUCATION INSTITUTIONS: RESEARCH ANALYSIS
The problem of improving the efficiency of managing higher education institutions has recently acquired special significance. Russia's confrontation with Western countries, which has significantly intensified in recent years, has led to the fact that Russian universities are no longer considered not only in the ratings of world foreign agencies, but also began to be excluded in general, as well as Russian papers from the collections of scientific research abroad. As a result, trying to remain on the lists of universities of foreign rating agencies, domestic universities perform largely useless work. In this regard, Russian universities lose time and money trying to achieve an increase in their position in foreign rankings. The paper aims to analyze the research of domestic and foreign scientists in the field of improving the effectiveness of ma-naging educational institutions and to develop conceptual provisions to improve the quality of managing higher education institutions in Russia. Materials and methods. The paper considers the most significant studies of Russian and foreign scholars, who have studied the issues of higher education institutions deve-lopment management in certain years, as well as some analytical articles and materials that aim to achieve similar results. It also uses well-known methods of analysis and comparison of various studies traditionally used in the field of management. Results. The paper presents the research analysis and comparison of works on improving the quality of management of Russian and foreign higher education institutions. Conclusion. The formation of conceptual provisions to improve the efficiency of managing higher education institutions in Russia should be focused not only and not so much on improving the ratings of universities, but on making their activities much more productive. This can only be achieved by ensuring that universities develop in accordance with the key objectives of the development of the respective regions and the country as a whole, and are focused not on secondary, but on key technical directions of promising the dynamics of the national economy.
MODERN METHODS OF COLLECTING AND ANALYZING EMPLOYERS REQUIREMENTS FOR TRAINING IT WORKERS
The development of the digital economy requires highly qualified IT specialists capable of meeting the growing demands of the market. Despite the significant increase in demand for IT professionals, the education system often fails to meet employers' expectations. The shortage of skilled personnel and the mismatch between graduates' competencies and market needs are key problems, which necessitate the development of new approaches to educational programs. Aim. The main objective of the research is to develop a concept for managing IT specialist training that takes into account modern employer requirements. This will optimize educational programs and improve the alignment of graduates' skills with current labor market demands. Materials and methods. To achieve the research objectives, machine learning methods and big data analysis were employed, along with vacancy monitoring from major online job platforms. Data on employer requirements were collected and systematized, and then compared with professional and educational standards. Natural Language Processing (NLP) technologies played a key role in the automated analysis of job vacancy texts. Results. The study resulted in the development of a concept for gathering and processing employer requirements to optimize IT specialist educational programs. A monitoring and analysis system for open data was created, allowing for regular updates to educational programs in line with labor market changes. The implementation of this system helps reduce the gap between graduates' professional competencies and employers' needs. Conclusion. The research results confirm that a systematic approach to managing IT specialist training, using employer requirements data, improves the quality of educational programs and increases graduates' competitiveness. This approach will help the education system more effectively adapt to the challenges of the digital economy, providing the labor market with in-demand specialists.
ELECTROMAGNETIC INTERFERENCE ATTENUATION IN A STRUCTURE WITH DOUBLE MODAL REDUNDANCY
This paper examines a method for enhancing the fault tolerance of radio-electronic equipment, termed modal redundancy, which combines the principles of redundancy and modal filtering. The essence of this method lies in utilizing strong electromagnetic coupling between two or more redundant conductors to mitigate electromagnetic interference. This approach offers several advantages, as the system can continue to operate even in the event of failure of one or more conductors, which is crucial for ensuring uninterrupted device operation. The modal redundancy method is effective in situations where it is necessary to minimize the risks of signal loss and reduce the impact of interference, making it valuable in various fields where high operational stability of equipment is required. Research Objective: To investigate the characteristics of asymmetric structures implemented using double modal redundancy and to eva¬luate their effectiveness under various operating conditions. Materials and Methods. To achieve the stated objective, electrodynamic and quasi-static analyses, as well as high-frequency measurements, were employed. The study was conducted in three stages: before the failure of the main conductor, after the first failure, and after the second failure, allowing for a detailed assessment of the system's behavior at diffe¬rent stages. Results. Frequency and time-domain characteristics of asymmetric structures with modal redundancy were obtained. The FSV method was used to analyze the data, enabling a comparative analysis of simulation and measurement data. The results demonstrated the high effectiveness of the method in mitigating electromagnetic interference and ensuring stable system operation, even when power is switched to redundant conductors. Conclusion. The presented investigated structures confirm the high practical applicability of the modal redundancy method for enhancing the fault tolerance of radio-electronic systems.
ABOUT ONE ALGORITHM OF ADAPTIVE CONTROL OF THE TURNING PROCESS USING ARTIFICIAL INTELLIGENCE METHODS
Increasing the efficiency of turning processes on CNC machines requires the development of special mathematical and information support for the implementation of adaptive control. It is proposed to use neural network approximators as models of the cutting process, constructed on the basis of experimental data obtained on a specific CNC machine during the processing of a specific material using a fixed tool. The purpose of the study: to study the issues of applying artificial intelligence methods for adaptive control of the turning process based on the obtained data on tool vibration. Materials and methods. An algorithm for solving the problem of optimal adaptive control is proposed, which ensures maximum productivity of a CNC machine in automatic mode. To organize feedback in adaptive control of the cutting process, sensor data on vibration acceleration of the cutting tool are continuously taken and processed. An estimate of the specific energy of the signal is calculated for a given time interval and a connection is established between it and the roughness of the workpiece surface. For this, a trained neural network is used, predicting the roughness value for given cutting modes based on the signal energy value about vibration. Results. The problem statement of adaptive control of the turning cutting process taking into account tool wear is proposed. An algorithm for intelligent processing of data on tool vibration acceleration during cutting is developed and a neural network is built that establishes a connection between the vibration level and surface roughness. An effective algorithm for solving the problem of optimal adaptive control is proposed. It allows real-time selection of cutting modes that ensure maximum cutting process productivity while meeting surface roughness constraints. Conclusion. The studied algorithms and models were tested on real data, which confirms the possibility of their use in the development of an intelligent information system for adaptive control of the turning process.
DETECTION OF ROTOR FAULTS IN INDUCTION MOTOR IN NON-STATIONARY CONDITIONS USING THE MATRIX PENCIL METHOD
Increasing the economic efficiency of production by reducing unplanned downtime and optimizing the maintenance of industrial equipment requires the development of diagnostic methods for such key equipment components as induction motors. In turn, the operating mode of the electric motor has a significant impact on the accuracy and reliability of diagnostics. In particular, the widely used method of motor current signature analysis (MCSA) has a number of limitations when the motor is operating at variable speed or load. Therefore, it is necessary to investigate frequency analysis methods that can extract motor defect signs from non-stationary current signals. Aim of the study: to apply matrix pencil method to motor current signals to extract signs of defect in the rotor bar of an induction motor under non-stationary mode of operation. Materials and methods. In this paper, the matrix pencil method is used, which has high spectral resolution and computational efficiency compared to Fourier transform based spectral analysis methods. Results. Numerical experiment shows that the matrix pencil method can extract frequencies and amplitudes of harmonics of the motor rotor defect with an accuracy of 2 % at low sampling rate (200 Hz) and small signal window length (0.25 s). Conclusion. The matrix pencil method allows to track the change in the frequency of the defect of the electric motor rotor and the increase in amplitude associated with an increase in the resistance of the rotor bar. Thus, the matrix pencil method can be applied in practice for diagnostics of induction motors.
ALGORITHMS OF IDENTIFICATION AND ELIMINATION OF MISTAKES IN KNOWLEDGE BASES OF EXPERT DIAGNOSTIC SYSTEMS
In this work diagnostic systems which on the functions are intended for the help to the user in permission of the following problem situation are considered: it is required to determine by a set of values of the private signs describing a condition of an object of a research. what properties this object has. Such tasks can arise, for example, in medical diagnostics (on a set of the symptoms describing a condition of the patient, the doctor has to take out the conclusion about the nature of a disease); in technical diagnostics (the reason of failure or breakage is determined by a number of indicators of work of a system); in geology (on the basis of data of geological exploration to draw a conclusion on existence of mineral deposits), etc. Unfortunately, for the solution of similar tasks use of methods of machine learning or deep machine learning therefore the only exit is use of expert mechanisms is not always possible. The research objective consists in forming of the knowledge base for the solution of problems of diagnostics which have to comprise decisive rules of the skilled experts allowing to build classification of all possible conditions of an object in previously structured problem area which classes are subsets of the states having the same property. Research methods. Methods of binary classification, the theory of counts are applied to the solution of problems of forming of the consistent knowledge base. When proofreading in classification of states there is no possibility of unambiguous carrying out necessary changes in classification of earlier identified states as elimination of mistakes cannot be carried out separately for each class. In this case to each state only one class of accessory therefore possible addition of a class of accessory to some states results in need of an exception of the accessory classes which are earlier appointed by it that is reached by use of the directed counts has to be appointed. Results. For holding poll of the specialist investigating the electroencephalogram initially all variety of possible states which are described by values of signs was created. In total, the quantity of similar states is equal to 216. After obtaining the expert opinion it was offered to it to estimate degree of probability of existence of a disease or its symptoms in this state, using terms “strong”, “average” and “weak” degrees of probability. It meant for the doctor that he was faced by a standard task of diagnosis. As a result of use of the rational procedure of poll during which the most informative state was provided it was succeeded to carry out classification of possible states for a short span and to receive answers to all questions. In total about 40 questions were asked. By means of a system, results of classification were reduced in the uniform knowledge base which included numbers of states, classes of accessory (diagnoses) and numbers of degree of probability for each of them. Such representation of knowledge takes place to be in a look because each state can be described by a feature set which have unambiguous compliance to its number. Thus, thanks to such data structure in the knowledge base of a system it is possible to calculate number from the knowledge base on set of symptoms of the patient and to define his diagnosis. Conclusion. To receive exhaustive and not contradictory set of rules which will be based on simple and clear actions from experts it is necessary to apply the offered approach to the solution of a problem of expert classification. In a diagnostic system the gained knowledge easily unites in the knowledge base which saves resources of memory and quickly finds a solution. Undoubtedly, the fact that the acquired classifications can be provided in a form of products, traditional for expert systems. As showed the experience of use of a diagnostic system offered by us a way of data structure, has higher performance in comparison with traditional.