Mathematics and Cybernetics - applied aspects

Mathematics and Cybernetics - applied aspects

In this issue:


Devising a method for forming a stable mobile cluster of the internet of things fog layer

The object of this study is the process of clustering the fog layer of the Internet of Things (IoT) with high and ultra-high density. The task to increase the stability of mobile components in the fog layer has been solved by modifying the clustering method. In the process of conducting research, an approach was devised to form the architecture of the mobile component in the fog layer of the IoT. Read more


Devising a universal optimization method under conditions of fuzzy initial data

The object of this study is an optimization method under conditions when the initial data (parameters of the system or the environment in which the system operates) are not precisely defined. The problem that arises in this case is related to the lack of universal mathematical methods that solve optimization problems under conditions of uncertainty of the initial data. To solve these problems, approaches are proposed based on the transformation of the initial fuzzy problems into clear problems of mathematical programming. Read more


Development and implementation of a numerical approach for optimal control of oscillations in coupled systems with distributed and lumped parameters

This study focuses on numerical solutions to control problems in oscillatory systems consisting of two distinct objects. The primary issue addressed is the effective modeling and control of oscillations in these systems, particularly through the interaction of two objects. The research yields significant results by demonstrating a method to transform the complex boundary value problem into a more manageable system of ordinary differential equations using the method of straight lines. Read more


The development of an electronic circuit simulation system using variable tabular bases

The object of the study is a system for electronic circuit simulation using variable tabular bases, which optimizes the calculation processes in complex circuits. The work addressed the problem of creating models of electronic circuits with a convenient description of components in a linear system of equations. A method for electronic circuit simulation using variable tabular bases is presented. Read more


Development of a combined neural network model for effective spectroscopic analysis

The object of this study is spectroscopic data from chemical, organic compounds, and physical experiments, characterized by signal complexity, low signal-to-noise ratio, and significant variability of acquisition conditions. The problem addressed is to improve the accuracy and stability of spectral data analysis in the tasks of identification and quantification of components, in particular under conditions of noise, variable baselines, and experimental parameters. Read more


Identifying the impact of the complexity of datasets in Bayesian optimized XGBoost on the performance of classifications for imbalanced class distribution datasets

This study explores how dataset complexity affects the performance of XGBoost models optimized using Bayesian methods, focusing on datasets characterized by imbalanced class distributions. The main challenge is accurately identifying minority classes, which are often misdiagnosed due to the dominance of majority classes, impairing predictive power. Additionally, dataset complexity, as indicated by the coefficient of variation (14.64?% to 85.68?%), does not consistently correlate with improved model performance, highlighting the need for more targeted methods. Read more


Development of heterogeneous data processing method in organizational and technical systems

The object of the study is heterogeneous data in organizational-technical systems. The subject of the study is the process of heterogeneous data processing. The problem of this study is enhancing the efficiency of heterogeneous data processing in organizational-technical systems while ensuring a predefined level of reliability, regardless of the volume of incoming data. A method for heterogeneous data processing in organizational-technical systems has been developed. Read more


Multi-objective optimization of a two-stage helical gearbox with double gears in second stage using saw technique to reduce bottom area and enhance efficiency

Two-stage helical gearboxes featuring two gears in the second stage are widely used across various industries. This gearbox design helps enhanced load capacity, increases consistent force distribution, and minimizes operational noise. One significant challenge in the design of this type of gearbox is the simultaneous optimization of multiple design criteria, including transmission efficiency and overall size. Optimizing gearbox design involves more than selecting an appropriate gear configuration; it necessitates a complete approach that balances performance with size, ensures sustainable operation, and minimizes manufacturing costs. Read more


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