Zhiren Tao

Hybrid PINN–GPR Method for Probabilistic Prediction of Concrete Creep Behavior

A novel hybrid method integrating physics-informed neural network (PINN) and Gaussian process regression (GPR) that enforces the B4 creep model as a physics-informed constraint by embedding its governing equations into the loss function, effectively incorporating physical knowledge into data-driven training.