Application of neural network for traffic forecasting in telecom networks

Telecommunication service providers must not only maintain a good understanding of the present state of the network, but also be able to forecast the future as accurately and precisely as possible. We focus on making traffic forecasting using neural network method. Two multi-layer perceptron neural network models are proposed respectively to make traffic prediction for two goals - one day´s 24-hour load shape prediction at a time and peak-load prediction of a day. The data collected from the real world is applied for the performance tests and the results show that our two models are both effective.