Abstract
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.
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