Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks

In this paper, the prediction of the energy transmission spectrum for layered periodic structures is studied. By considering three cases of geometric parameters and physical parameters changing individually or simultaneously, a deep back propagation (BP) neural network is constructed to realize accu...

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Autores principales:	LIU Chenxu, YU Guilan
Formato:	article
Lenguaje:	ZH
Publicado:	Editorial Office of Journal of Shanghai Jiao Tong University 2021
Materias:	layered periodic structure deep back propagation (bp) neural network radial basis function (rbf) neural network energy transmission spectrum attenuation domain Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
Acceso en línea:	https://doaj.org/article/e3147e33e4744f91a5d9666d1ddbd668
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spelling	oai:doaj.org-article:e3147e33e4744f91a5d9666d1ddbd6682021-11-04T09:35:15ZPrediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks1006-246710.16183/j.cnki.jsjtu.2019.242https://doaj.org/article/e3147e33e4744f91a5d9666d1ddbd6682021-01-01T00:00:00Zhttp://xuebao.sjtu.edu.cn/CN/10.16183/j.cnki.jsjtu.2019.242https://doaj.org/toc/1006-2467In this paper, the prediction of the energy transmission spectrum for layered periodic structures is studied. By considering three cases of geometric parameters and physical parameters changing individually or simultaneously, a deep back propagation (BP) neural network is constructed to realize accurate prediction of the energy transmission spectrum of layered periodic structure. A comparison of the predicted results with those obtained by the radial basis function (RBF) neural network verifies the effectiveness of the proposed method.LIU ChenxuYU GuilanEditorial Office of Journal of Shanghai Jiao Tong Universityarticlelayered periodic structuredeep back propagation (bp) neural networkradial basis function (rbf) neural networkenergy transmission spectrumattenuation domainEngineering (General). Civil engineering (General)TA1-2040Chemical engineeringTP155-156Naval architecture. Shipbuilding. Marine engineeringVM1-989ZHShanghai Jiaotong Daxue xuebao, Vol 55, Iss 01, Pp 88-95 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	layered periodic structure deep back propagation (bp) neural network radial basis function (rbf) neural network energy transmission spectrum attenuation domain Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
spellingShingle	layered periodic structure deep back propagation (bp) neural network radial basis function (rbf) neural network energy transmission spectrum attenuation domain Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989 LIU Chenxu YU Guilan Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
description	In this paper, the prediction of the energy transmission spectrum for layered periodic structures is studied. By considering three cases of geometric parameters and physical parameters changing individually or simultaneously, a deep back propagation (BP) neural network is constructed to realize accurate prediction of the energy transmission spectrum of layered periodic structure. A comparison of the predicted results with those obtained by the radial basis function (RBF) neural network verifies the effectiveness of the proposed method.
format	article
author	LIU Chenxu YU Guilan
author_facet	LIU Chenxu YU Guilan
author_sort	LIU Chenxu
title	Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
title_short	Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
title_full	Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
title_fullStr	Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
title_full_unstemmed	Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks
title_sort	prediction of energy transmission spectrum of layered periodic structures by neural networks
publisher	Editorial Office of Journal of Shanghai Jiao Tong University
publishDate	2021
url	https://doaj.org/article/e3147e33e4744f91a5d9666d1ddbd668
work_keys_str_mv	AT liuchenxu predictionofenergytransmissionspectrumoflayeredperiodicstructuresbyneuralnetworks AT yuguilan predictionofenergytransmissionspectrumoflayeredperiodicstructuresbyneuralnetworks
_version_	1718444995645538304

Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks

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