During the experimental study, a pronounced beating and sealing of the side surface of the tubular, cylindrical blanks was recorded. It is established that cracks appear and develop in the central part of the lateral surface, i.e., it are destroyed. This fact confirms the claim that the destruction of tubular, cylindrical blanks of some materials begins on the side surface. It is established that the bases of analytical dependencies between the components of deformations describe the obtained results of the experimental study of SR tubular, cylindrical blanks within the error of the experimental data, which made it possible to construct a number of mathematical models for the purpose of further study of the SDS and the method of their determination.

Artificial intelligence is employed for solving complex scientific, technical, and practical problems. Such artificial intelligence techniques as neural networks, fuzzy systems, and genetic and evolutionary algorithms are widely used for communication systems management, optimization, and prediction. Artificial intelligence approach provides optimized results in a challenging task of call admission control, handover, routing, and traffic prediction in cellular networks. 5G mobile communications are designed as heterogeneous networks, whose important requirement is accommodating great numbers of users and the quality of service satisfaction. Call admission control plays a significant role in providing the desired quality of service. An effective call admission control algorithm is needed for optimizing the cellular network system. Many call admission control schemes have been proposed. The paper proposes a methodology for developing a genetic neurofuzzy controller for call admission in 5G networks. Performance of the proposed admission control is evaluated through computer simulation.

The mathematical modeling of the Chaotic Colpitts Oscillator with two stages is carried out in the paper. The following results of mathematical modeling are obtained: oscillator's phase portrait in the planes of normalized dynamic variables; oscillator's phase portraits in the spaces of normalized dynamic variables; time diagrams of generated chaotic oscillations; amplitude-frequency and phase-frequency characteristics of generated chaotic oscillations.

The accuracy of ultrasonic rangefinders is crucial for mobile robotic navigation systems, yet environmental factors such as temperature, humidity, atmospheric pressure, and wind conditions can influence ultrasonic speed in the air. The primary objective is to investigate how environmental factors influence the output signal of an ultrasonic emitter and to develop a method for improving the accuracy of distance measurements in both outdoor and indoor settings. The research employs a combination of theoretical modeling, statistical analysis, and experimental validation. The research employs an ultrasonic rangefinder integrated with environmental sensors (BME280, Bosch Sensortec GmbH, Kusterdingen, Germany) and wind sensors (WMT700, WINDCAP^®, Vaisala Oyj, Vantaa, Finland) to account for environmental influences. Experimental studies were conducted using a prototype ultrasonic rangefinder, and statistical analysis (Student’s t-test) was performed on collected data. The results of estimation by Student’s t-test for 256 measurements demonstrate the maximum effect of air temperature and the minimum effect of relative air humidity on a piezoelectric emitter output signal both outdoors and indoors. In addition, wind parameters affect the rangefinder’s operation. The maximum range of obstacle detection depends on the reflection coefficient of the material that covers the obstacle. The results align with theoretical expectations for highly reflective surfaces. A cascade-forward artificial neural network model was developed to refine distance estimations. This study demonstrates the importance of considering environmental factors in ultrasonic rangefinder systems for mobile robots. By integrating environmental sensors and using statistical analysis, the accuracy of distance measurements can be significantly improved. The results contribute to the development of more reliable navigation systems for mobile robots operating in diverse environments.