Traffic trends analysis using neural networks

An application of time series prediction, to traffic forecasting in ATM networks, using neural nets is described. One key issue, the number of data points needed to be included in the input representation to the net is discussed from a theoretical point of view, and the results are applied in the model under discussion. Experimental results are discussed and analysed.