neural networks

Управління мережами мобільного зв’язку 5G за допомогою використання технологій штучного інтелекту

The article is devoted to the problem of excessive traffic of base station cells. In order to reduce the
impact of this problem on the quality of services of mobile network operators, it is proposed to use
artificial intelligence (AI) technology to analyze and predict the load on the network. AI is great for
wireless environments, as it has a lot of data available for analysis and obtaining certain patterns.
The article proposes a model of machine learning and neural network architecture for forecasting
the load on 5G cells.

Analysis of Algorithms for Searching Objects in Images Using Convolutional Neural Network

The problem of finding objects in images using modern computer vision algorithms has been considered. The description of the main types of algorithms and methods for finding objects based on the use of convolutional neural networks has been given. A comparative analysis and modeling of neural network algorithms to solve the problem of finding objects in images has been conducted. The results of testing neural network models with different architectures on data sets VOC2012 and COCO have been presented.

Acquisition and Processing of Data in CPS for Remote Monitoring of the Human functional State

Data acquisition and processing in cyber-physical system for remote monitoring of the human functional state have been considered in the paper. The data processing steps, strategies for multi-step forecasting evaluation metrics and machine learning algorithms to be implemented have been analysed and described. What is important, this way it will be possible to track the condition of the sick and response to the health changes in advance.


It is shown that for the pro­ces­sing of in­tensi­ve da­ta flows in in­dustry (ma­na­ge­ment of techno­lo­gi­cal pro­ces­ses and complex ob­jects), energy (op­ti­mi­za­ti­on of lo­ad in po­wer grids), mi­li­tary af­fa­irs (techni­cal vi­si­on, mo­bi­le ro­bot traf­fic control, cryptog­raphic da­ta pro­tec­ti­on), transport (traf­fic ma­na­ge­ment and en­gi­ne), me­di­ci­ne (di­se­ase di­ag­no­sis) and instru­men­ta­ti­on (pat­tern re­cog­ni­ti­on and control op­ti­mi­za­ti­on) the re­al-ti­me hardwa­re neu­ral net­works with high ef­fi­ci­ency of eq­uipment use sho­uld be appli­ed.

Evolution of Artificial Intelligence on the Background of the Progress in Computer Sciences and Engineering (Review of the Monograph: Mainzer, K. (2020). Artificial Intelligence – When Do Machines Take Over? Berlin, Heidelberg: Springer)

The review examines the content and main problems of the English-language monograph of the German scientist and philosopher, President of the European Academy of Sciences and Arts, founder of the Munich Center for Social Technologies (MCTS), Honorary Professor of the Technical University of Munich, Professor of Mathematics and Natural Sciences at the Univercity of Tübingen Klaus Mainzer.

Synchronization of time invariant uncertain delayed neural networks in finite time via improved sliding mode control

This paper explores the finite-time synchronization problem of delayed complex valued neural networks with time invariant uncertainty through improved integral sliding mode control.  Firstly, the master-slave complex valued neural networks are transformed into two real valued neural networks through the method of separating the complex valued neural networks into real and imaginary parts.  Also, the interval uncertainty terms of delayed complex valued neural networks are converted into the real uncertainty terms.  Secondly, a new integral sliding mode surface is designed by employing the ma

Зменшення кількості хибних викликів під час розв’язання задачі детектування полум'я у відеопотоці з використанням глибоких згорткових нейронних мереж

In this paper, we develop a new approach for detecting fire in images based on convolutional neural networks. Cascade structure, which provides improved efficiency of recognition in images with low resolution and objects that can visually resemble flames, was proposed. We have performed an experimental comparison with the modern method of objects detecting Faster R-CNN. As a result of the experiments, it was found that performance of fire recognition improved on average by 20%.

Інтелектуальні компоненти інтегрованих автоматизованих систем управління для енергетичних систем

Досліджено особливості інтелектуальних компонент інтегрованих автоматизо- ваних систем управління. Розглянуто створення інтелектуальної компоненти ІАСУ для енергетичних систем. Запропоновано нейромережні методи прогнозування споживання електроенергії підприємством на основі машини геометричних перетворень. Наведено результати проведених експериментів.

Дослідження та аналіз методів забезпечення надвисокої роздільної здатності зображень на основі машинного навчання

In this article the methods of image superresolution based on machine learning are
investigated. The work of different groups of these methods are analyzed. Basic features of this
methods are describing. On the basis of practical experiments comparative analysis (by the
criterion PSNR) of the superresolution methods in the case of one input image from different
classes were conducted. Experimentally found that the best results are obtained in case of
using the method based on the convolutional neural network. Despite the requirement on the

Методи спектроскопії та обробка даних спектрального аналізу

This article provides an analysis of modern methods of spectroscopy in medicine, examined their classification. Conducted a review of portable spectroscopic systems, analysis of the advantages and disadvantages of their use. Analysis of components for spectroscopic analysis. Review of methods of the spectrum classification. Brought a conceptual diagram of processing the received data and its classification. Review of applications portable spectroscopic systems.