Automatic differentiation might bring about numerical instability in the solution of partial differential equations (PDEs). Therefore, to address this challenge, an MTN-PINN …
To address the challenges in core-cavity design for injection molds-namely reliance on manual experience, low automation, and difficulty in ensuring manufacturability-this paper …
Physics–Informed Neural Networks (PINNs) have demonstrated efficacy in solving both forward and inverse problems for nonlinear partial differential equations (PDEs). However, they …
This is a detailed study note for the “SCI Paper Writing Video Course” offered by AiMi Editor. The original English title of this public course is Writing in the Sciences on …