In the paper a neural simulator of steam power unit is presented as an example of appli-cation of artificial neural networks (ANN) for modeling complex technical objects. A set ofone-directional back-propagation networks was applied to simulate distribution of main steam flow parameters in the cycle’s crucial points for a broad range of loading. A verygood accuracy and short computation time was obtained. The advantages make the simula-tor useful for on-line diagnostic applications where short response time is very important. The most important features of the simulator, main phases of its elaboration and a certain amount of experience gained from solving the task was presented to make the practical application of the method in question more familiar
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