A Network Traffic Prediction Model Based on Quantum Inspired PSO and Neural Network

Abstract

The network traffic prediction model is the foundation of network performance analysis and designing. Aiming at limitation of the conventional network traffic time series prediction model and the problem that BP algorithms easily plunge into local solution, an optimization algorithm-PSO-QI which combine particle swarm optimization (PSO) and the quantum principle is proposed, and can alleviate the premature convergence validly. Then, the parameters of BP neural network were optimized and the time series of network traffic data was modeled and forecasted based on BP neural network and PSO-QI. Experiments showed that PSOQI-BP neural network has better precision and adaptability compared with the traditional neural network.