Tension prediction by using ANN and SOM in heavy facilities

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86085019" target="_blank" >RIV/61989100:27240/11:86085019 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/NaBIC.2011.6089653" target="_blank" >http://dx.doi.org/10.1109/NaBIC.2011.6089653</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NaBIC.2011.6089653" target="_blank" >10.1109/NaBIC.2011.6089653</a>

Result language
angličtina
Original language name
Tension prediction by using ANN and SOM in heavy facilities
Original language description
Diagnostic systems based on mathematical models of material damaging process can be used to collect necessary information on trends and/or level of material and function damage. This paper is focused on the improvement of a particular part of the power plant diagnostic system. It describes some alternatives based on Artifical Neural Networks and Self-Organising Maps. Finally, this can help to eliminate the damages of power plant facilities. 2011 IEEE.
Czech name
—
Czech description
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Project
<a href="/en/project/FR-TI1%2F086" target="_blank" >FR-TI1/086: New design approach of energetic components and steel structures with high utility parameters, JSC</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2011 Third World Congress on Nature and Biologically Inspired Computing
ISBN
978-1-4577-1122-0
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
582-587
Publisher name
IEEE
Place of publication
New York
Event location
Salamanca
Event date
Oct 19, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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