基于混沌理论的煤矿监控网络流量时间序列的预测

针对目前煤矿监控网络的流量增大趋势,为了改进和提高网络的QoS质量,提出了基于混沌时间序列预测网络流量的方法.从相空间重构,用互信息量法和虚假临近点法确定了延迟时间和嵌入维数,用小数据量法求解了最大Lyapunov指数,由此证明了网络流量时间序列的混沌特性,并且建立相应模型,成功地对其做出了预测.仿真结果表明,该方法具有较高的准确度.

Based on Chaos Theory to Predict the Series Time of Mine Monitoring and Control Network Traffic

Coal mine for the current trend of increasing network traffic monitoring,in order to improve and enhance the quality of the network QoS,we propose a chaotic time series prediction based on the network traffic.From the phase space reconstruction,with the mutual information and false near the point of law determined by the delay time and embedding dimension,with a small amount of data the maximum Lyapunov index method,which proved that the chaotic time series of network traffic characteristics,and the establi...