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What is Implicit Runge Kutta Physics Informed Neural Network For Parameter Identification of Structural Systems about?

This study introduces an implicit Runge-Kutta physics-informed neural network (PINN) based on the Radau IIA discretization scheme for parameter identification in structural systems. The proposed Radau IIA PINN integrates physical laws directly into a recurrent neural network architecture, enhancing robustness and accuracy while reducing computational costs compared to traditional PINNs. Numerical simulations demonstrate its effectiveness in identifying structural deterioration under sparse and noisy measure

Author

anshul

Language

EN