Pages that link to "Item:Q2691025"
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The following pages link to Machine learning-assisted parameter identification for constitutive models based on concatenated loading path sequences (Q2691025):
Displaying 7 items.
- CPINet: parameter identification of path-dependent constitutive model with automatic denoising based on CNN-LSTM (Q1982319) (← links)
- Application of general regression neural network in identifying interfacial parameters under mixed-mode fracture (Q2083815) (← links)
- Machine learning for accelerating macroscopic parameters prediction for poroelasticity problem in stochastic media (Q2226818) (← links)
- Optimization framework for calibration of constitutive models enhanced by neural networks (Q2848328) (← links)
- Automated model discovery for skin: discovering the best model, data, and experiment (Q6094670) (← links)
- A machine learning approach to automate ductile damage parameter selection using finite element simulations (Q6141143) (← links)
- Automatic parameter identification of a shape memory alloy model using characteristic experimental data points (Q6558113) (← links)
