Omsk State Transport University

The relevance of the article is determined by the radical changes that are currently taking place in the entire system of secondary vocational education. Increasing the emphasis on the practical training of students, increasing the volume of educational and industrial practices with the mandatory implementation of the envisaged work at real production facilities, postponing the beginning of the formation of professional competencies of students for the period of studying general educational disciplines by conducting binary classes, joint work the development of materials for classes by teachers of general education disciplines and teachers of professional modules of the educational program of secondary vocational education, the maximum approximation of the content of the intermediate certification of students to their future profession and, finally, the conduct of the state final certification in the form of a demonstration exam — all these innovations require new approaches to the educational process from teachers, the introduction of changes in the existing order, the use of new forms and methods of conducting classes and close interaction with enterprises of the industry.The article presents and analyzes the experience of conducting a demonstration exam in the Omsk Technical School of Railway Transport — a structural unit of secondary vocational education of the Federal State Budgetary Educational Institution of Higher Education of Omsk State Transport University. The features of the organization of the demonstration exam, the results achieved by students of the three specialties in which it was conducted are considered, the important role of practical training of students and the role of Russian Railways in organizing and conducting the demonstration exam are noted.

The article examines the issues of comparative analysis of statistics of service losses to subscribers in urban and rural telecommunications networks. The issue of increasing the efficiency of telecommunications network management using forecasting methods based on processing statistics of telecommunications network equipment states is considered

The article analyzes the organization of mass entertainment events and highlights the problem of delivering creative teams to performance sites and venues. It conducts an analysis of related literature and creates a mathematical model for scheduling the delivery of creative teams to venues, taking into account their systematic movement. A software for automatic vehicles distribution, delivering creative teams to performance sites, is proposed. Methodology of a systems approach, modern concepts of transport logistics and supply chain management, as well as economic, mathematical and statistical methods, were used to analyze the problem and draw conclusions.

Purpose: To select and verify methods and algorithms of machine learning to build dynamic models of a train energy-efficient movement in real time. Earlier, the use of DC electric locomotives for driving freight trains was assessed and the factors influencing the energy-efficient train movement were identified. This paper is devoted to the latest innovations in the field of automated train control within the framework of the JSC “Russian Railways” grant project for young scientists to carry out scientific research aimed at creating new equipment and technologies for railway transport. Methods: Optimization methods for machine learning were applied using model nonlinear dynamic systems. Results: The Levenberg-Marquardt method has been found most appropriate for determining the optimal position of the train driver controller by using recurrent neural network training. Graphical dependences of error histograms and total mean square error (MSE) variations in the process of artificial neural network training have been obtained. Practical significance: The results of the research can be used in the development of hardware and software systems using artificial intelligence methods and algorithms aimed at energy-efficiency improvement in transportation process.

Background: This study discusses the use of wavelet transform for processing acoustic signals when diagnosing power transformers. A simulator with various defects was used to explore the application of continuous wavelet transform. The study also outlines an algorithm for obtaining signal standards to identify different types of defects. Aim. To develop a mathematical model for constructing reference acoustic control signals when processing data from a simulator with various defects. These signals will be used to identify and diagnose defects in real power transformers during their operation. Methods. The study introduces expressions for signal transformation, presents acoustic control signals, and explains the formation of reference signals. It also describes the process of recognizing the closest signals in form, corresponding to different types of defects. Results. The key results include expressions for signal transformation, acoustic control signals, and the formation of reference signals. The closest matching signals were identified, enabling accurate recognition of different defect types. Conclusion. The research proposes a method for processing acoustic control signals, allowing the reproduction of various insulation defects of power transformers and the recognition of such defects according to the proposed parameters of the wavelet transform.

Aim. Improving the efficiency of AC traction power supply systems. Solving challenges in testing technical and technological solutions using simulation modeling of their operating modes. Methods and Materials. The research is based on a simulation model designed to test algorithms for regulating the operation of electric power storage devices within the traction power supply system. The tasks are solved using the following methods: system method, analytical method, and statistical modeling method. Results. The proposed simulation model enabled the testing of an algorithm regulating an electric power storage device. The simulation provided results for active power regulation using the voltage levels in the contact network. The results included calculated oscillograms and voltages, along with their effective values for both charge and discharge modes. Conclusion. The results obtained can be used to compare the effectiveness of different methods for regulating electric power storage devices in AC traction power supply systems.

The authors describe the further building of the critical infrastructure of the modern confrontation between Russia in the SMO through cooperation with friendly partners against the collective West in the field of building up non-linear responses to conducting operations on the battlefield and in the shops of defense and ICT companies.They also analyze the required correction of the military-industrial complex sector, which should move away from the previously adopted standards of excessive conversion and focus on the development of new generation high-tech products for use in military operations, in space and further digitalization of the Russian economy.The ongoing bankruptcies of big tech and digital start-ups in Silicon Valley and the growing demand for Chinese and Indian scientific schools and materials science base in matters of occupying basic and defining positions in the fragmentation chains of the future Industry 4.0 are assessed.and on the BRICS and SCO platforms, as the basis for building a global robotic-humanoid way of life in the world of monetary and military zones.

The Fuzzy Cognitive Map (FCM) method was developed by B. Kosko to extend cognitive maps, which are widely used to represent knowledge in the social sciences. Several algorithms have been proposed for training FCMs. The main objective of the training procedure is to nd a setting of FCM weights that will bring the FCM to a desired stable state. This is achieved by minimizing a well-de ned objective function. The established algorithms heavily depend on the initial approximation of the weight matrix, which is provided by experts. One of the methods for training FCMs is based on particle swarm optimization (PSO). PSO is used to determine the appropriate weight matrices for the system by minimizing a given objective function.