Neural Network Models of Time Series of Network Traffic Intensities

The paper presents the results of building neural network predictive models of the occupancy of the channel packet data. The problem is solved by the example of time series observations of the intensities at the commutator switch port. The above algorithm for constructing a neural network model based on the determination of the fractal dimension of the time series. The autoregressive model is constructed as a parallel model. The developed models are compared in accordance with the rated value of entered criteria for assessing the accuracy of the forecast.