Notice of RetractionApplication of genetic algorithm and RBF neural network in network flow prediction

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Time series forecasting is the main method in network flow prediction. RBF neural network is capable of universal approximation, which not only has fast training velocity, but also can solve the local minima problem. Thus, network flow prediction technology based on genetic algorithm and RBF neural network is presented in the paper. And the training parameters are adjusted by genetic algorithm. Network flow data about 40 points can be applied to study the superiority of genetic algorithm and RBF neural network neural network compared with normal RBF neural network. By the analysis of application case, it can be seen that the forecasting performance of genetic algorithm and RBF neural network is better than that of normal RBF neural network.