...Tong Zhu; Qiye Zheng; Yanglong Lu Physics-informed neural networks (PINNs) are a novel approach to solving partial differential equations (PDEs) through deep learning. They offer a unified manner for solving forward and inverse problems, which is beneficial for various engineering problems...

... detection nonlinear regression inverse problem Newton’s law of cooling Michaelis–Menten model Lineweaver–Burk plot big data and analytics computational foundations for engineering optimization data-driven engineering inverse methods for engineering applications machine learning for engineering...