Neural networks for computing in the elastoplastic analysis of structures

DOI10.1007/BF00987122zbMath0823.73077OpenAlexW1994339607MaRDI QIDQ1892025

S. Kortesis, A. V. Avdelas, Panagiotis D. Panagiotopoulos

Publication date: 9 November 1995

Published in: Meccanica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00987122

zbMATH Keywords

Hopfield modelparameter identification problemlearning probleminequality conditionsquadratic programming problems

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Thin bodies, structures (74K99) Plastic materials, materials of stress-rate and internal-variable type (74C99)

Related Items (4)

On the parameter identification problem for failure criteria in anisotropic bodies ⋮ Hardening Plasticity Approximated via Anisotropic Elasticity. The Fokker‐Planck Equation in a Neural Network Environment ⋮ Plasticity including the Bauschinger effect, studied by a neural network approach ⋮ Generalised hardening plasticity approximated via anisotropic elasticity: A neural network approach

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