Heavy facilities tension prediction using flexible neural trees
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86085108" target="_blank" >RIV/61989100:27240/11:86085108 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/SoCPaR.2011.6089276" target="_blank" >http://dx.doi.org/10.1109/SoCPaR.2011.6089276</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SoCPaR.2011.6089276" target="_blank" >10.1109/SoCPaR.2011.6089276</a>
Alternative languages
Result language
angličtina
Original language name
Heavy facilities tension prediction using flexible neural trees
Original language description
In this article we show the usage of soft-computing methods to solve the real problem of computation of tension in facilities working under very hard conditions in industrial environment. Because the classical mathematical approaches such as Finite Element Method (FEM) are very time consuming, the more progressive soft-computing methods are on the place. We have proposed two step algorithm based on Flexible Neural Tree (FNT) and Particle Swarm Optimization (PSO) which is more efficient then typical approach (FEM). Flexible neural tree is hierarchical neural network like structure, which is automatically created and optimized using evolutionary like algorithms to solve the given problem. This is very important, because it is not necessary to set the structure and the weights of neural networks prior the problem is solved. The accuracy of proposed technique is good enough to be used in real environments.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
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)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2011 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2011
ISBN
978-1-4577-1194-7
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
396-401
Publisher name
IEEE
Place of publication
New York
Event location
Dalian
Event date
Oct 14, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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