An adaptive collocation physics-informed neural networks for multidimensional heat conduction problems in complex geometries
Physics-Informed Neural Networks (PINNs) have emerged as an effective framework for solving partial differential equations (PDEs) by embedding physical laws directly into the learning process. However, variable thermal conductivity and discontinuous solutions introduce heterogeneous coefficients, sharp gradients and...