基于混沌理论的网络流量BP神经网络预测

Study on Internet Traffic Forecast of BP Neutral Network Based on Chaos Theory

应用相空间重构技术,论证了网络流量存在混沌现象,并计算了实际网络流量的关联维,Lyapunov指数;在此基础上对网络流量时间序列建立BP神经网络模型对网络流量进行预测,实例表明,和FARIMA(p,d,q)模型相比,基于混沌理论的BP神经网络模型有较好的预测能力,并具有较长的预测步长。

With phase space reconstruction,the paper demonstrates the Internet traffic chaos phenomena lies in Internet traffic,and computes some parameters such as correlative dimension,Lyapunov exponent.Based on this,the paper constructs the BP neutral network model to forecast the Internet traffic.Comparing with FARIMA(p,d,q) model,the BP neutral network model has the same ability of forecast and has longer space of forecast.