Finite Element Physics Informed Neural Network
Abstract
This research enhances a novel finite element physics-informed neural network (FE-PINN) framework in order to optimize efficiency and results. The enhancements include tuning hyperparameters and considering new methodology in constructing the model architecture. This study seeks to achieve improved results and further the potential and applications of incorporating finite element discretization into PINN approaches to civil infrastructure analysis.
Finite Element Physics Informed Neural Network
This research enhances a novel finite element physics-informed neural network (FE-PINN) framework in order to optimize efficiency and results. The enhancements include tuning hyperparameters and considering new methodology in constructing the model architecture. This study seeks to achieve improved results and further the potential and applications of incorporating finite element discretization into PINN approaches to civil infrastructure analysis.