About: Microplane Model Parameters Estimation Using Neural Networks     Goto   Sponge   NotDistinct   Permalink

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  • 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.
  • 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. (en)
Title
  • Microplane Model Parameters Estimation Using Neural Networks
  • Microplane Model Parameters Estimation Using Neural Networks (en)
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  • Microplane Model Parameters Estimation Using Neural Networks
  • Microplane Model Parameters Estimation Using Neural Networks (en)
skos:notation
  • RIV/68407700:21110/06:00122645!RIV11-MSM-21110___
http://linked.open...avai/riv/aktivita
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  • Z(MSM6840770003)
http://linked.open...vai/riv/dodaniDat
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  • 485673
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  • RIV/68407700:21110/06:00122645
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  • concrete; evolutionary algorithms; inverse analysis; neural networks; sensitivity analysis (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FEC81778D79C]
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  • Lisabon
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  • Lisboa
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  • Proceedings of III-rd European Conference on Computational Mechanics
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  • Kučerová, Anna
  • Lepš, Matěj
  • Zeman, Jan
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http://linked.open...n/vavai/riv/zamer
number of pages
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  • Technical University of Lisbon
https://schema.org/isbn
  • 1-4020-4994-3
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  • 21110
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