Inverse FEM Analysis I: Stochastic Training of Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F05%3APU54992" target="_blank" >RIV/00216305:26110/05:PU54992 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
čeština
Original language name
Inverse FEM Analysis I: Stochastic Training of Neural Network
Original language description
The paper suggests a new approach of inverse analysis to obtain parameters of FEM computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of FEM computational model and the stochastic training of artificial neural network. Identification parameters play the role of basic random variables witch a scatter reflecting the physical range of possible values. Novelty of the approach is the utilization of efficient small-sample ssimulation method Latin Hypercube Sampling (LHS) used for training of neural network.
Czech name
Inverse FEM Analysis I: Stochastic Training of Neural Network
Czech description
The paper suggests a new approach of inverse analysis to obtain parameters of FEM computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of FEM computational model and the stochastic training of artificial neural network. Identification parameters play the role of basic random variables witch a scatter reflecting the physical range of possible values. Novelty of the approach is the utilization of efficient small-sample ssimulation method Latin Hypercube Sampling (LHS) used for training of neural network.
Classification
Type
D - Article in proceedings
CEP classification
JM - Structural engineering
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GA103%2F04%2F2092" target="_blank" >GA103/04/2092: Model identification and optimization at material a structural levels</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2005
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Inženýrská mechanika 2005
ISBN
80-85918-93-5
ISSN
—
e-ISSN
—
Number of pages
12
Pages from-to
233-244
Publisher name
—
Place of publication
Svratka, Czech Republic
Event location
Svratka
Event date
May 9, 2005
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
—