Abstract
Network traffic flow prediction model is fundamental to the network performance evaluation and the design of network control scheme which is crucial for the success of high-speed networks. Aiming at shortcoming of the conventional network traffic time series prediction model and the problem that BP training algorithms easily plunge into local solution, a network traffic prediction model based on wavelet neural network and PSO-QI is presented in the paper. Firstly, the quantum principle obtained from Quantum PSO(QPSO)has been combined with standard PSO to form a new hybrid algorithm called PSO with Quantum Infusion(PSO-QI). Then, the parameters of wavelet neural network were optimized with PSO-QI and the time series of network traffic data was modeled and predicted based on wavelet neural network and PSO-QI. Experiments showed that PSOQI-wavelet neural network has better precision and adaptability compared with the traditional neural network.