Microplane Model Parameters Estimation Using Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F06%3A00122645" target="_blank" >RIV/68407700:21110/06:00122645 - 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
Microplane Model Parameters Estimation Using Neural Networks
Original language description
A procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed.
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
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
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 III-rd European Conference on Computational Mechanics
ISBN
1-4020-4994-3
ISSN
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e-ISSN
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Number of pages
14
Pages from-to
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Publisher name
Technical University of Lisbon
Place of publication
Lisboa
Event location
Lisabon
Event date
Jun 5, 2006
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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