КФУ. Карточка публикации. Recovery of parameters of a homogeneous elastic layer using neural networks

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RECOVERY OF PARAMETERS OF A HOMOGENEOUS ELASTIC LAYER USING NEURAL NETWORKS

Форма представления

Статьи в зарубежных журналах и сборниках

Год публикации

2017

Язык

английский

Авторы, сотрудники КФУ

Валеева Алсу Анваровна, автор

Тумаков Дмитрий Николаевич, автор

Авторы, студенты КФУ

Хайруллина Диана Марсовна, автор

Библиографическое описание на языке оригинала

Tumakov D.N., Khairullina D.M., Valeeva A.A. Recovery of parameters of a homogeneous elastic layer using neural networks // Journal of Fundamental and Applied Sciences, 2017, 9(2S), 1202-1220. (doi 10.4314/jfas.v9i2s.791)

Аннотация

The problem of recovery of parameters of an elastic uniform layer is considered. The solution method of this problem is proposed by means of neural networks. For the input network parameters, amplitudes of transmitted or reflected waves are chosen. We consider the output parameter of network density and longitudinal speed of the environment filling a layer. Three types of neurons activation function are chosen: piecewise-linear, sigmoid and radial function (Gauss's function). The following algorithms of perseptron training are considered: the backpropagation algorithm and the genetic algorithm. In the genetic algorithm, the crossover method, in which the next gene is selected equiprobable and incidental from genes of the ancestors located in the same position is chosen. Then genes of a new chromosome with small probability are exposed to mutations at a small value.

Ключевые слова

parameter recovery, uniform elastic layer, neural network

Название журнала

JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES

URL

http://www.jfas.info/index.php/jfas/article/view/3021

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https://repository.kpfu.ru/?p_id=166164

Полная запись метаданных

Поле DC	Значение	Язык
dc.contributor.author	Валеева Алсу Анваровна	ru_RU
dc.contributor.author	Тумаков Дмитрий Николаевич	ru_RU
dc.contributor.author	Хайруллина Диана Марсовна	ru_RU
dc.date.accessioned	2017-01-01T00:00:00Z	ru_RU
dc.date.available	2017-01-01T00:00:00Z	ru_RU
dc.date.issued	2017	ru_RU
dc.identifier.citation	Tumakov D.N., Khairullina D.M., Valeeva A.A. Recovery of parameters of a homogeneous elastic layer using neural networks // Journal of Fundamental and Applied Sciences, 2017, 9(2S), 1202-1220. (doi 10.4314/jfas.v9i2s.791)	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/?p_id=166164	ru_RU
dc.description.abstract	JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES	ru_RU
dc.description.abstract	The problem of recovery of parameters of an elastic uniform layer is considered. The solution method of this problem is proposed by means of neural networks. For the input network parameters, amplitudes of transmitted or reflected waves are chosen. We consider the output parameter of network density and longitudinal speed of the environment filling a layer. Three types of neurons activation function are chosen: piecewise-linear, sigmoid and radial function (Gauss's function). The following algorithms of perseptron training are considered: the backpropagation algorithm and the genetic algorithm. In the genetic algorithm, the crossover method, in which the next gene is selected equiprobable and incidental from genes of the ancestors located in the same position is chosen. Then genes of a new chromosome with small probability are exposed to mutations at a small value.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	parameter recovery	ru_RU
dc.subject	uniform elastic layer	ru_RU
dc.subject	neural network	ru_RU
dc.title	Recovery of parameters of a homogeneous elastic layer using neural networks	ru_RU
dc.type	Статьи в зарубежных журналах и сборниках	ru_RU