This paper presents dependence of the vortex core axial velocity and vortex center position on clearance in a tip leakage vortex (TLV) for different angles using a system of neural networks (NNs) simulation in which the Resilient Propagation (RPROP) algorithm is applied. These studies are simulation of the vortex core axial velocity and vortex center position as a function of clearance at different angles. The system was trained on the available data of the two cases. The trained NN shows a better agreement with that of an experimental data in two cases; vortex core axial velocity and vortex center position.