Annotation: The article provides a review of various approaches to defining integrated territorial development and classification of the effects of their use. The experience of using intelligent information systems as the main tool for planning and implementing integrated territorial development projects is analyzed. The practices of using intelligent information systems, including geographic information and expert systems, and decision support systems are considered. An analysis of practices and trends in the use of artificial intelligence to solve integrated territorial development problems was carried out. Evaluation of the socio-economic efficiency of integrated urban development activities is an important stage in project planning and implementation. This allows us to determine how useful and beneficial these activities will be for the city and its residents. The evaluation methods used have a number of shortcomings related to the insufficient completeness and reliability of the initial information, as well as insufficient consideration of mutual cause-and-effect relationships. The use of special methods allows for a more objective and high-quality assessment of the development of the territory, as well as an assessment of the effectiveness of investments and decisions made. This is important for both government agencies and business structures that participate in the development of the territory. Intelligent information systems play an important role in the development of cities and territories, providing opportunities for analysis, forecasting and decision making based on various data and methods. When analyzing data, the relationships and dependencies between various factors of territorial development are taken into account, as well as probabilities and risks. A comparative analysis of intelligent information systems used in the world was carried out. Each of these systems has its own characteristics and capabilities, which may be important when planning the integrated development of territories depending on the tasks set. But there are currently no systems that would completely cover the management and economic processes in urban development. Their advantages and disadvantages are considered. In conclusion the prospects for using intelligent information systems for making management decisions that ensure the integrated development of territories.

Annotation: In relation to computing systems (CS) and computer networks (CN), some research results devoted to solving the scientific problem of developing widely applicable probabilistic models, software, technological and methodological solutions focused on predicting and rational risk control in system engineering are reviewed. The paper covers the following issues: analysis of existing approaches to risk assessment and control, improvement and standardization of probabilistic models for predicting and rational risk control in the lifecycle of various systems, development of software and technological solutions that ensure risk prediction and justification of proactive measures to counter threats in the autonomous and remote mode of application of CS and CS, for these solutions - development of typical methods for the use of advanced probabilistic models in CS and CS, and, finally, the development of recommendations and demonstration examples for reducing and maintaining risks within acceptable limits based on the use of the created infrastructure and technology to support risk-oriented system engineering. Some illustrative examples are given.

Annotation: Objectives: System analysis of the functionality and reliability of the navigation system of an autonomous surface vessel. The main focus is on the study and modeling of the state of the vessel during its motion, including position, speed and heading angle, by analyzing the data provided by ambient light sensors, the transition from measurements to the representation of the state of the vessel in a two-dimensional navigation coordinate system is carried out. Part of the analysis is the study of how to convert the data from the inertial coordinate system to the navigational coordinate system, which is related to the consideration of angular parameters and nonlinear dynamics of the system. In addition, the study focuses on evaluating the effectiveness of data filtering algorithms, such as the unfiltered Kalman filter (UKF), and their ability to adequately reflect the ship's state under complex and changing external influences. The aim of the article is to conduct a systematic analysis of the processes of receiving and processing navigation system data, to identify possible error factors and to develop approaches to ensure the accuracy of estimation and stability of ship control in various operating conditions. Methods: The main results of the work were obtained using methods of mathematical analysis and modeling. Results: The navigation system of an autonomous vessel is considered with emphasis on the system analysis of its main components and algorithms. The model of motion in the navigation coordinate system based on acceleration and angular velocity data provided by inertial sensors is specified. The feasibility of transforming the measurements through the rotation matrix using the heading angle is shown, which allowed to reduce errors and improve the representation of motion parameters. The effectiveness of the unfiltered Kalman filter (UKF) in conditions of nonlinearity and external disturbances is analyzed, and its ability to provide stable and accurate estimation of the ship's state is confirmed. Conclusions: A proposed motion model using Kalman filter (UKF) to combine sensor data to improve navigational accuracy.

Annotation: Modern and future aircraft are characterized by an increased degree of electrification of onboard systems and the use of electromechanical systems to ensure critical functions of the aircraft flight control system. Widespread implementation of onboard electromechanical systems requires their safe and efficient operation, for which purpose it is assumed that the aircraft is equipped with an early diagnostics system for faults. Electromechanical systems of an aircraft, the closed control loop of which is implemented based on feedback signals for the speed or movement of the output link, are subject to high requirements for the quality of regulation, including under the action of mechanical load. Deterioration of the characteristics of an electromechanical system is associated with degradation processes that develop in individual components and can be determined based on data obtained both in the passive mode during a typical flight and in the active mode when processing specified control signals between flights in ground conditions. Modern artificial intelligence methods allow their effective use in creating algorithms for early diagnostics of electromechanical systems for classification and forecasting of technical condition using big data containing valuable information about work processes associated with the development of faults. To obtain such data, the main scenarios of operation of electromechanical systems were studied in the work, allowing to obtain representative samples. To ensure an automated data collection process using signals transmitted via standard interfaces of information interaction of the integrated control system with end devices, as well as from additionally used sensors, data accumulation methods were developed and studied using the results of modeling, testing and operation. Based on the obtained data, it is possible to assess the degradation of static and dynamic characteristics of electromechanical systems and determine their significance in classifying the technical condition for localizing malfunctions and performing condition-based maintenance. For this purpose, methods for processing the obtained data were developed and studied and the practical application of the results for subsequent on-board integration of the diagnostic system was assessed.

Annotation: In the modern world, the banking sector faces a number of challenges related to risk management in project investments. These risks can be of different nature, including financial, operational, credit and market. With the development of technology and the introduction of artificial intelligence in various areas of business, the emphasis on the use of AI methods in risk management in the banking sector is becoming increasingly significant. Artificial intelligence has the potential to significantly improve the processes of data analysis, forecasting and decision making, which, in turn, can improve the efficiency of risk management. However, the introduction of AI methods also leads to the emergence of new problems and challenges. One of the key issues is the need for high-quality data for training AI models, as well as overcoming issues related to ethical aspects and transparency of algorithms. The specifics of banking activities require not only high accuracy of algorithms, but also compliance with strict regulatory standards, which adds complexity to the process of integrating AI methods. This article discusses the issue of using artificial intelligence in project management risks in a bank. The article analyzes AI methods such as machine learning and big data analytics, their use in credit risk assessment, preliminary research and monitoring of various stages of the project cycle. Particular attention is paid to how these technologies can help in identifying potential threats and responding to them as quickly as possible. The purpose of the article is to reveal the advantages and disadvantages of approaches to applying artificial intelligence in risk management in IT projects of banks. We will try to identify in which cases the use of AI methods can significantly improve risk management processes, and in which cases it can entail additional difficulties and risks. The study will present examples of successful application of AI methods in the banking sector, as well as substantiate the key factors contributing to the successful integration of technologies. This will allow a deeper understanding of the difficulties and benefits associated with the implementation of artificial intelligence in risk management, which is an important aspect for modern banking policy and strategy.

Annotation: The article discusses the design of software and hardware systems based on personal computers using locally connected hardware accelerators based on graphics processors (GPUs) or programmable logic integrated circuits (FPGAs) with FPGA or APSOC architecture. Since the set of peripheral devices included in a personal computer is limited, it determines the achievable data transfer rate. Thus, the computing performance of hardware accelerators added to the complex must be consistent with the technically achievable speed of transmitting input data to the accelerator and returning the calculated values. Interfacing with a personal computer also requires the presence of a corresponding interface controller in the connected accelerator. Options for connecting FPGA-based accelerators to a personal computer using the PCI Express interface to form a software and hardware complex designed for tasks such as digital signal processing, information security and regular expression recognition, implemented on the basis of an accelerator with parallel architecture, are considered.

Annotation: Nowadays work is underway on a series of preprinted national standards that should prepare the normative and formalized field for the implementation of SMART standards. With the intensive development of this area of domestic standardization, a number of proposals arise related to the approaches on which the authors of this series of preprinted national standards rely. The article makes some suggestions, based on the best practices of modern software engineering, to improve the overall level of the field under consideration. During the development process, it is necessary to pay special attention to such aspects as the development of a typing system over the space of standardization objects, as well as the organization of a system of connections between similar objects. In addition, it is also important to dwell on the division of levels of abstraction and responsibility between each of the levels of the model structure of such documents. In addition, the article is based on the results of the review of the revision of the "Smart (SMART) standards. Architecture and data formats" from January 2024 and relies on the well-known experience of implementing and researching requirement-oriented formats, namely their focus on the degree of expressiveness of the requirements themselves. At the time of publication, this preprinted national standard has been revised based on the results of public discussion.