Development of a method of structural-parametric assessment of the object state

A method of structural and parametric assessment of the object state has been developed. The essence of the method is to provide an analysis of the current state of the object under analysis. The key difference of the developed method is the use of advanced procedures for processing undefined initia...

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Autores principales:	Qasim Abbood Mahdi, Ruslan Zhyvotovskyi, Serhii Kravchenko, Ihor Borysov, Oleksandr Orlov, Ihor Panchenko, Yevhen Zhyvylo, Artem Kupchyn, Dmytro Koltovskov, Serhii Boholii
Formato:	article
Lenguaje:	EN RU UK
Publicado:	PC Technology Center 2021
Materias:	artificial neural networks neural network training modified algorithm of evolution strategies Technology (General) T1-995 Industry HD2321-4730.9
Acceso en línea:	https://doaj.org/article/2273d319abbe4a6b8a46987137015a70
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spelling	oai:doaj.org-article:2273d319abbe4a6b8a46987137015a702021-11-04T14:06:45ZDevelopment of a method of structural-parametric assessment of the object state1729-37741729-406110.15587/1729-4061.2021.240178https://doaj.org/article/2273d319abbe4a6b8a46987137015a702021-10-01T00:00:00Zhttp://journals.uran.ua/eejet/article/view/240178https://doaj.org/toc/1729-3774https://doaj.org/toc/1729-4061A method of structural and parametric assessment of the object state has been developed. The essence of the method is to provide an analysis of the current state of the object under analysis. The key difference of the developed method is the use of advanced procedures for processing undefined initial data, selection, crossover, mutation, formation of the initial population, advanced procedure for training artificial neural networks and rounding coordinates. The use of the method of structural-parametric assessment of the object state allows increasing the efficiency of object state assessment. An objective and complete analysis is achieved using an advanced algorithm of evolution strategies. The essence of the training procedure is the training of synaptic weights of the artificial neural network, the type and parameters of the membership function, the architecture of individual elements and the architecture of the artificial neural network as a whole. An example of using the proposed method in assessing the operational situation of the troops (forces) grouping is given. The developed method is 30–35 % more efficient in terms of the fitness of the obtained solution compared to the conventional algorithm of evolution strategies. Also, the proposed method is 20–25 % better than the modified algorithms of evolution strategies due to the use of additional improved procedures according to the criterion of fitness of the obtained solution. The proposed method can be used in decision support systems of automated control systems (artillery units, special-purpose geographic information systems). It can also be used in DSS for aviation and air defense ACS, DSS for logistics ACS of the Armed Forces of UkraineQasim Abbood MahdiRuslan ZhyvotovskyiSerhii KravchenkoIhor BorysovOleksandr OrlovIhor PanchenkoYevhen ZhyvyloArtem KupchynDmytro KoltovskovSerhii BoholiiPC Technology Centerarticleartificial neural networksneural network trainingmodified algorithm of evolution strategiesTechnology (General)T1-995IndustryHD2321-4730.9ENRUUKEastern-European Journal of Enterprise Technologies, Vol 5, Iss 4 (113), Pp 34-44 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU UK
topic	artificial neural networks neural network training modified algorithm of evolution strategies Technology (General) T1-995 Industry HD2321-4730.9
spellingShingle	artificial neural networks neural network training modified algorithm of evolution strategies Technology (General) T1-995 Industry HD2321-4730.9 Qasim Abbood Mahdi Ruslan Zhyvotovskyi Serhii Kravchenko Ihor Borysov Oleksandr Orlov Ihor Panchenko Yevhen Zhyvylo Artem Kupchyn Dmytro Koltovskov Serhii Boholii Development of a method of structural-parametric assessment of the object state
description	A method of structural and parametric assessment of the object state has been developed. The essence of the method is to provide an analysis of the current state of the object under analysis. The key difference of the developed method is the use of advanced procedures for processing undefined initial data, selection, crossover, mutation, formation of the initial population, advanced procedure for training artificial neural networks and rounding coordinates. The use of the method of structural-parametric assessment of the object state allows increasing the efficiency of object state assessment. An objective and complete analysis is achieved using an advanced algorithm of evolution strategies. The essence of the training procedure is the training of synaptic weights of the artificial neural network, the type and parameters of the membership function, the architecture of individual elements and the architecture of the artificial neural network as a whole. An example of using the proposed method in assessing the operational situation of the troops (forces) grouping is given. The developed method is 30–35 % more efficient in terms of the fitness of the obtained solution compared to the conventional algorithm of evolution strategies. Also, the proposed method is 20–25 % better than the modified algorithms of evolution strategies due to the use of additional improved procedures according to the criterion of fitness of the obtained solution. The proposed method can be used in decision support systems of automated control systems (artillery units, special-purpose geographic information systems). It can also be used in DSS for aviation and air defense ACS, DSS for logistics ACS of the Armed Forces of Ukraine
format	article
author	Qasim Abbood Mahdi Ruslan Zhyvotovskyi Serhii Kravchenko Ihor Borysov Oleksandr Orlov Ihor Panchenko Yevhen Zhyvylo Artem Kupchyn Dmytro Koltovskov Serhii Boholii
author_facet	Qasim Abbood Mahdi Ruslan Zhyvotovskyi Serhii Kravchenko Ihor Borysov Oleksandr Orlov Ihor Panchenko Yevhen Zhyvylo Artem Kupchyn Dmytro Koltovskov Serhii Boholii
author_sort	Qasim Abbood Mahdi
title	Development of a method of structural-parametric assessment of the object state
title_short	Development of a method of structural-parametric assessment of the object state
title_full	Development of a method of structural-parametric assessment of the object state
title_fullStr	Development of a method of structural-parametric assessment of the object state
title_full_unstemmed	Development of a method of structural-parametric assessment of the object state
title_sort	development of a method of structural-parametric assessment of the object state
publisher	PC Technology Center
publishDate	2021
url	https://doaj.org/article/2273d319abbe4a6b8a46987137015a70
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Development of a method of structural-parametric assessment of the object state

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