Development of prognostic neural network models based on non-positional coding for automatic control systems

The article is devoted to the discussion of the problems of development of predictive neural network models based on the residual number system and the use of modular arithmetic to improve the quality of automatic control systems by adding to the control algorithms a prognostic component, which is e...

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Главные авторы:	Tikhonov, E. E., Тихонов, Э. Е., Sosin, A. I., Сосин, А. И.
Формат:	Статья
Язык:	English
Опубликовано:	Institute of Electrical and Electronics Engineers Inc. 2019
Темы:	Neural network control systems Neural network forecasting Positional number system (PNS) Residue number system (RNS) Control system
Online-ссылка:	https://www.scopus.com/record/display.uri?eid=2-s2.0-85061709671&origin=resultslist&sort=plf-f&src=s&st1=Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems&st2=&sid=5ae6e1ef2618948862f9a63c7746ec40&sot=b&sdt=b&sl=123&s=TITLE-ABS-KEY%28Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/4623
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spelling	ir-20.500.12258-46232024-10-18T10:48:21Z Development of prognostic neural network models based on non-positional coding for automatic control systems Tikhonov, E. E. Тихонов, Э. Е. Sosin, A. I. Сосин, А. И. Neural network control systems Neural network forecasting Positional number system (PNS) Residue number system (RNS) Control system The article is devoted to the discussion of the problems of development of predictive neural network models based on the residual number system and the use of modular arithmetic to improve the quality of automatic control systems by adding to the control algorithms a prognostic component, which is especially important for astatic control objects. The possibility of implementing neural network training algorithms in the residual number system is shown, which allows to significantly accelerate the work of these algorithms, which is especially important when adding new functionality to automatic control systems in the form of prognostic neural network models 2019-03-04T09:28:49Z 2019-03-04T09:28:49Z 2018 Статья Tikhonov, E.E., Sosin, A.I. Development of Prognostic Neural Network Models Based on Non-Positional Coding for Automatic Control Systems // 2018 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2018. - 2018. - Номер статьи 8602839 https://www.scopus.com/record/display.uri?eid=2-s2.0-85061709671&origin=resultslist&sort=plf-f&src=s&st1=Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems&st2=&sid=5ae6e1ef2618948862f9a63c7746ec40&sot=b&sdt=b&sl=123&s=TITLE-ABS-KEY%28Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems%29&relpos=0&citeCnt=0&searchTerm= http://hdl.handle.net/20.500.12258/4623 en 2018 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2018 application/pdf application/pdf Institute of Electrical and Electronics Engineers Inc.
institution	СКФУ
collection	Репозиторий
language	English
topic	Neural network control systems Neural network forecasting Positional number system (PNS) Residue number system (RNS) Control system
spellingShingle	Neural network control systems Neural network forecasting Positional number system (PNS) Residue number system (RNS) Control system Tikhonov, E. E. Тихонов, Э. Е. Sosin, A. I. Сосин, А. И. Development of prognostic neural network models based on non-positional coding for automatic control systems
description	The article is devoted to the discussion of the problems of development of predictive neural network models based on the residual number system and the use of modular arithmetic to improve the quality of automatic control systems by adding to the control algorithms a prognostic component, which is especially important for astatic control objects. The possibility of implementing neural network training algorithms in the residual number system is shown, which allows to significantly accelerate the work of these algorithms, which is especially important when adding new functionality to automatic control systems in the form of prognostic neural network models
format	Статья
author	Tikhonov, E. E. Тихонов, Э. Е. Sosin, A. I. Сосин, А. И.
author_facet	Tikhonov, E. E. Тихонов, Э. Е. Sosin, A. I. Сосин, А. И.
author_sort	Tikhonov, E. E.
title	Development of prognostic neural network models based on non-positional coding for automatic control systems
title_short	Development of prognostic neural network models based on non-positional coding for automatic control systems
title_full	Development of prognostic neural network models based on non-positional coding for automatic control systems
title_fullStr	Development of prognostic neural network models based on non-positional coding for automatic control systems
title_full_unstemmed	Development of prognostic neural network models based on non-positional coding for automatic control systems
title_sort	development of prognostic neural network models based on non-positional coding for automatic control systems
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2019
url	https://www.scopus.com/record/display.uri?eid=2-s2.0-85061709671&origin=resultslist&sort=plf-f&src=s&st1=Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems&st2=&sid=5ae6e1ef2618948862f9a63c7746ec40&sot=b&sdt=b&sl=123&s=TITLE-ABS-KEY%28Development+of+Prognostic+Neural+Network+Models+Based+on+Non-Positional+Coding+for+Automatic+Control+Systems%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/4623
work_keys_str_mv	AT tikhonovee developmentofprognosticneuralnetworkmodelsbasedonnonpositionalcodingforautomaticcontrolsystems AT tihonovée developmentofprognosticneuralnetworkmodelsbasedonnonpositionalcodingforautomaticcontrolsystems AT sosinai developmentofprognosticneuralnetworkmodelsbasedonnonpositionalcodingforautomaticcontrolsystems AT sosinai developmentofprognosticneuralnetworkmodelsbasedonnonpositionalcodingforautomaticcontrolsystems
_version_	1842245707816239104

Development of prognostic neural network models based on non-positional coding for automatic control systems

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