Use of neural networks library for material defect detection diagnosis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F11%3A50000393" target="_blank" >RIV/62690094:18450/11:50000393 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.springerlink.com/content/mg5r3156026297x2/" target="_blank" >http://www.springerlink.com/content/mg5r3156026297x2/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-21762-3_58" target="_blank" >10.1007/978-3-642-21762-3_58</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Use of neural networks library for material defect detection diagnosis

Popis výsledku v původním jazyce

Aim of this project is to prepare support for design and realization of application, which is developed in object orientated programming language C#. This application classifies data that are obtained within industrial processes. Data used in this project was received during measurement of material diagnostics and its structural defects. Core of developed application is based on neural networks design, which is capable to classify whether the material has defect or not. Before classification itself it is necessary to set structural parameters of the neural network to obtain a good quality results. Afterwards application outputs are compared with outputs from Statistica programme, which is also used for classification purposes.

Název v anglickém jazyce

Use of neural networks library for material defect detection diagnosis

Popis výsledku anglicky

Aim of this project is to prepare support for design and realization of application, which is developed in object orientated programming language C#. This application classifies data that are obtained within industrial processes. Data used in this project was received during measurement of material diagnostics and its structural defects. Core of developed application is based on neural networks design, which is capable to classify whether the material has defect or not. Before classification itself it is necessary to set structural parameters of the neural network to obtain a good quality results. Afterwards application outputs are compared with outputs from Statistica programme, which is also used for classification purposes.

Druh

D - Stať ve sborníku

CEP obor

JB - Senzory, čidla, měření a regulace

OECD FORD obor

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Projekt

<a href="/cs/project/GAP403%2F10%2F1310" target="_blank" >GAP403/10/1310: SMEW - Inteligentní prostředí na pracovištích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Electric and electronics (EEIC 2011)

ISBN

978-3-642-21761-6

ISSN

1876-1100

e-ISSN

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Počet stran výsledku

8

Strana od-do

447-454

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Nanchang

Datum konání akce

20. 6. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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