This contribution is focused on the insurance of control system data communication via neural network technologies in
connection with classical methods used in expert systems. The solution proposed defines a way of data element identification in
transfer networks, solves the transformation of their parameters for neural network input and defines the type and architecture of
a suitable neural network. This is supported by experiments with various architecture types and neural network activation
functions and followed by subsequent real environment tests. A functional system proposal with possible practical application is
the result