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  3. Reinforced machine networks, dependency, neural fis_scads

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    1Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning
     

    J. Gerritzen, A. Hornig, P. Winkler, and M. Gude. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3, page 1252--1259. European Society for Composite Materials (ESCM), (Jul 2, 2024)21st European Conference on Composite Materials, ECCM 21 ; Conference date: 02-07-2024 Through 05-07-2024.
    a month ago by @scadsfct
    show all tags
    • area_architectures
    • topic_engineering
    • Convolutional
    • Direct
    • FIS_scads
    • Fiber
    • Machine
    • Strain
    • dependency,
    • identification,
    • learning,
    • networks,
    • neural
    • parameter
    • plastics
    • rate
    • reinforced
     
      area_architecturestopic_engineeringConvolutionalDirectFIS_scadsFiberMachineStraindependency,identification,learning,networks,neuralparameterplasticsratereinforced
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