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  • A multi-objective formulation of a nonlinear material model identification is presented. Since the material is tested on the basis of several tests, the multi-objective optimization with objectives for errors in individual tests' identification is a logic solution. Two optimization algorithms are implemented and compared. The first one is based on mean error function and an application of the single-objective genetic algorithm GRADE. In the second approach, for each test an error function will be defined, which allows to emphasize individual contributions of those tests. To optimize this problem, the multi-objective genetic algorithm NSGA-II is employed.
  • A multi-objective formulation of a nonlinear material model identification is presented. Since the material is tested on the basis of several tests, the multi-objective optimization with objectives for errors in individual tests' identification is a logic solution. Two optimization algorithms are implemented and compared. The first one is based on mean error function and an application of the single-objective genetic algorithm GRADE. In the second approach, for each test an error function will be defined, which allows to emphasize individual contributions of those tests. To optimize this problem, the multi-objective genetic algorithm NSGA-II is employed. (en)
Title
  • Multi-Objective Identification of Nonlinear Material Model
  • Multi-Objective Identification of Nonlinear Material Model (en)
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  • Multi-Objective Identification of Nonlinear Material Model
  • Multi-Objective Identification of Nonlinear Material Model (en)
skos:notation
  • RIV/68407700:21110/12:00198567!RIV13-MSM-21110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(TA01030733), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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  • 152414
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21110/12:00198567
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  • parameter estimation; multi-objective optimization; NSGA-II; GRADE; clustering, data mining (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [C3AC83A5F492]
http://linked.open...v/mistoKonaniAkce
  • Prague
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 3rd Conference Nano and Macro Mechanics NMM 2012
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  • Lepš, Matěj
  • Pospíšilová, Adéla
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number of pages
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  • České vysoké učení technické v Praze. Fakulta stavební
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  • 978-80-01-05097-2
http://localhost/t...ganizacniJednotka
  • 21110
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