Numerical simulation of neural network components of controlling and measuring systems

The article deals with the problem of calculating the fault tolerance of neural network components of industrial controlling and measuring systems used in mechanical engineering. We have formulated a general approach to developing methods for quantitative determination of the level of the fault tolerance of artificial neural networks with any structure and function. We have studied the fault tolerance of four artificial feedforward neural networks as well as the correlation between the result of determining the fault tolerance level and a selected performance parameter of artificial neural networks.