Automatic differentiation might bring about numerical instability in the solution of partial differential equations (PDEs). Therefore, to address this challenge, an MTN-PINN …
Physics–Informed Neural Networks (PINNs) have demonstrated efficacy in solving both forward and inverse problems for nonlinear partial differential equations (PDEs). However, they …
The Ekman equation is a fundamental model for describing the wind stress response in the ocean's upper layer,with its key parameters—the vertical eddy viscosity coefficient (VEVC) …
