Abstract The magnetic inversion problem described by differential equations is an important research direction in plasma physics. Recently, neural networks have emerged as a widely used tool to address this problem. However, in the process of solving forward problem, structure-preserving algorithms have not been considered. In this study, we develop a framework of magnetic field inversion neural network embedded volume-preserving algorithm (MINN+VPA) by applying the volume-preserving algorithms