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Application of artificial neural networks in chosen glass laminates properties prediction

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28110%2F13%3A43870264" target="_blank" >RIV/70883521:28110/13:43870264 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-1-4614-3558-7_95" target="_blank" >http://dx.doi.org/10.1007/978-1-4614-3558-7_95</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-1-4614-3558-7_95" target="_blank" >10.1007/978-1-4614-3558-7_95</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of artificial neural networks in chosen glass laminates properties prediction

  • Original language description

    The article deals with applications of the artificial neural networks at the evaluation of chosen material's properties (sample thickness, sample shape) measured by electronic speckle pattern interferometry. We have investigated the dependence of the generated mode frequency as a function of sample thickness as well as the sample shape of glass laminate samples. Obtained experimental results for differently shaped glass laminate samples are compared with those of artificial neural networks and finite element method simulation. The coincidence of both experimental and simulated results is very good. Copyright 2013 Springer Science+Business Media.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JI - Composite materials

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Electrical Engineering

  • ISBN

    978-1-4614-3558-7

  • ISSN

    1876-1100

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1113-1120

  • Publisher name

    Springer Netherlands

  • Place of publication

    Nizozemsko

  • Event location

    Bridgeport

  • Event date

    Dec 3, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article