摘要
对煤矿监测网络流量异变预测可以提高网络的服务质量(QoS),降低网络拥塞的发生率。该文分析了煤矿监测网络中各信息流量的特点,提出了以SCADA类信息流作为混沌指标信号,采用Lyapunov指数法验证指标量的混沌特性,利用Duffing振子求解相变点的策动力幅值ad并构建了预测模型。通过仿真预测和实测数据比较,误差在0.036 632之间,验证了该预测方法准确可靠。
Prediction of the traffic mutation in network for mine monitoring can enhance quality of service（QoS） and reduce network congestion.In view of the characteristics of traffic in mine monitoring network,data acquisition（SCADA） information is selected as indicator of chaotic signal and Lyapunov exponent method is used to verify the chaotic characters of the indicator.Duffing oscillator is employed to calculate the amplitude of the critical threshold of the oscillator and a predicting model is constructed.The error between simulation results and real data is between ？0.036 632,validating the accuracy and reliability of the predicting method.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2012年第3期424-428,共5页
Journal of University of Electronic Science and Technology of China
基金
陕西省教育厅自然科学专项(2010JK663)
