Fig. 22

An illustration of a PINN structure. x and y are respectively the input and output of the neural network. The loss function of a PINN can contain two parts, namely the data-driven loss term and the physics law loss term. The output of the neural network can be directly compared to the ground truth data, which results in the data-driven loss term. In addition, the output of the neural network can be also substituted into the physics laws in terms of governing equations, which contributes to the physics law loss term