Hardening Plasticity Approximated via Anisotropic Elasticity. The Fokker‐Planck Equation in a Neural Network Environment
DOI10.1002/zamm.19950751103zbMath0860.73013OpenAlexW2035511728MaRDI QIDQ5689881
Panagiotis D. Panagiotopoulos, Pericles S. Theocaris
Publication date: 15 January 1997
Published in: ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/zamm.19950751103
convergenceyield surfacesparameter identification problemsupervised and unsupervised learning algorithms
System identification (93B30) Anisotropy in solid mechanics (74E10) Plastic materials, materials of stress-rate and internal-variable type (74C99) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31) Neural nets applied to problems in time-dependent statistical mechanics (82C32)
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