TY - JOUR A2 - Kattan, Ahmed AU - Zhang, Kun AU - Hu, Zhao AU - Gan, Xiao-Ting AU - Fang, Jian-Bo PY - 2016 DA - 2016/03/10 TI - A Network Traffic Prediction Model Based on Quantum-Behaved Particle Swarm Optimization Algorithm and Fuzzy Wavelet Neural Network SP - 4135056 VL - 2016 AB - Due to the fact that the fluctuation of network traffic is affected by various factors, accurate prediction of network traffic is regarded as a challenging task of the time series prediction process. For this purpose, a novel prediction method of network traffic based on QPSO algorithm and fuzzy wavelet neural network is proposed in this paper. Firstly, quantum-behaved particle swarm optimization (QPSO) was introduced. Then, the structure and operation algorithms of WFNN are presented. The parameters of fuzzy wavelet neural network were optimized by QPSO algorithm. Finally, the QPSO-FWNN could be used in prediction of network traffic simulation successfully and evaluate the performance of different prediction models such as BP neural network, RBF neural network, fuzzy neural network, and FWNN-GA neural network. Simulation results show that QPSO-FWNN has a better precision and stability in calculation. At the same time, the QPSO-FWNN also has better generalization ability, and it has a broad prospect on application. SN - 1026-0226 UR - https://doi.org/10.1155/2016/4135056 DO - 10.1155/2016/4135056 JF - Discrete Dynamics in Nature and Society PB - Hindawi Publishing Corporation KW - ER -