Neural network technology for processing of signals from technical objects control means

The paper presents a technology based on an ensemble of neural networks that solves the problem of predicting a multidimensional time series of telemetry data. A distinctive feature of this is the possibility of additional training in the case of analyzing parameters in a non-stationary environment,...

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Main Authors: A. A. Doudkin, Y. Y. Marushko
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2019-06-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
Subjects:
Online Access:https://doklady.bsuir.by/jour/article/view/1016
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author A. A. Doudkin
Y. Y. Marushko
author_facet A. A. Doudkin
Y. Y. Marushko
author_sort A. A. Doudkin
collection DOAJ
description The paper presents a technology based on an ensemble of neural networks that solves the problem of predicting a multidimensional time series of telemetry data. A distinctive feature of this is the possibility of additional training in the case of analyzing parameters in a non-stationary environment, providing operational processing of the entire set of telemetry parameters of the technical object, increasing the accuracy of identification and prediction of the state of the object by telemetric information with incomplete and noisy input data. This reduces the costs of monitoring the status and behavior of the control object.
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publisher Educational institution «Belarusian State University of Informatics and Radioelectronics»
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spelling doaj.art-8b68b053ac144b98a4f78f47dcdbf1682023-03-13T07:33:18ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482019-06-010585911015Neural network technology for processing of signals from technical objects control meansA. A. Doudkin0Y. Y. Marushko1Объединенный институт проблем информатики НАН Беларуси, Республика БеларусьОбъединенный институт проблем информатики НАН Беларуси, Республика БеларусьThe paper presents a technology based on an ensemble of neural networks that solves the problem of predicting a multidimensional time series of telemetry data. A distinctive feature of this is the possibility of additional training in the case of analyzing parameters in a non-stationary environment, providing operational processing of the entire set of telemetry parameters of the technical object, increasing the accuracy of identification and prediction of the state of the object by telemetric information with incomplete and noisy input data. This reduces the costs of monitoring the status and behavior of the control object.https://doklady.bsuir.by/jour/article/view/1016neural networksensemble of neural networkstelemetry datastate prediction
spellingShingle A. A. Doudkin
Y. Y. Marushko
Neural network technology for processing of signals from technical objects control means
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
neural networks
ensemble of neural networks
telemetry data
state prediction
title Neural network technology for processing of signals from technical objects control means
title_full Neural network technology for processing of signals from technical objects control means
title_fullStr Neural network technology for processing of signals from technical objects control means
title_full_unstemmed Neural network technology for processing of signals from technical objects control means
title_short Neural network technology for processing of signals from technical objects control means
title_sort neural network technology for processing of signals from technical objects control means
topic neural networks
ensemble of neural networks
telemetry data
state prediction
url https://doklady.bsuir.by/jour/article/view/1016
work_keys_str_mv AT aadoudkin neuralnetworktechnologyforprocessingofsignalsfromtechnicalobjectscontrolmeans
AT yymarushko neuralnetworktechnologyforprocessingofsignalsfromtechnicalobjectscontrolmeans