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.