KFU. Card publication. Recovery of parameters of a homogeneous elastic layer using neural networks

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

RECOVERY OF PARAMETERS OF A HOMOGENEOUS ELASTIC LAYER USING NEURAL NETWORKS

Form of presentation

Articles in international journals and collections

Year of publication

2017

Язык

английский

Authors, employees of KFU

Valeeva Alsu Anvarovna, author

Tumakov Dmitriy Nikolaevich, author

Authors, students KFU

Khayrullina Diana Marsovna, author

Bibliographic description in the original language

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)

Annotation

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.

Keywords

parameter recovery, uniform elastic layer, neural network

The name of the journal

JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES

URL

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

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=166164&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Valeeva Alsu Anvarovna	ru_RU
dc.contributor.author	Tumakov Dmitriy Nikolaevich	ru_RU
dc.contributor.author	Khayrullina Diana Marsovna	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/eng/?p_id=166164&p_lang=2	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	Articles in international journals and collections	ru_RU