neural networks

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.

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.

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

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%.

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.

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

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.

The problem of inspection, control of parameters and diagnostics of the state of surface metal layers of underground pipelines with consideration of influence of corrosive environment is considered.