Approximation-based approaches to identification of material model parameters
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F11%3A00187048" target="_blank" >RIV/68407700:21110/11:00187048 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Approximation-based approaches to identification of material model parameters
Original language description
Increasing complexity of material models requires increasing efficiency and robustness of identification strategies. The presented contribution presents a comparison of several different approaches to parameters identification based on artificial neuralnetworks or genetic programming.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GPP105%2F11%2FP370" target="_blank" >GPP105/11/P370: Artificial neural networks in multi-scale modelling of transport processes in heterogeneous materials</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
NMM 2011 Nano & Macr Mechanics
ISBN
978-80-01-04892-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
86-92
Publisher name
České vysoké učení technické v Praze, Fakulta stavební
Place of publication
Praha
Event location
Praha
Event date
Oct 6, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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