二元时间序列模型预测3G网络接通率  

Connection Rate Prediction Method by Bivariate Time Series

作　　者：王喆[1] 张丽翠[1] 黄丽平 

机构地区：[1]吉林大学通信工程学院,长春130012 [2]吉林大学计算机科学与技术学院,长春130012

出　　处：《吉林大学学报（信息科学版）》2015年第2期219-222,共4页Journal of Jilin University（Information Science Edition）

摘　　要：为提高对网络性能预判的准确度,提出了运用多元时间序列的相关性计算方法,时间序列的模糊化方法和模糊规则矩阵的构建方法,建立了一种基于二元时间序列的接通率预测模型,将拥塞率序列融入到对接通率的预测过程中。该方法克服了传统网络性能指标预测方法中,只考虑单一时间序列,不考虑其他变量与待预测变量的相关性的弊端。仿真实验结果表明,该模型能够实现网络接通率的有效预测,为网络性能综合预测提供理论基础和新方案。提高了预测精度。In order to improve the accuracy of network performance pre ju based on time series connected to two yuan rate, congestion rate sequence into the prediction process of docking pass rate. The calculation method of correlation using multivariate time series, fuzzy time series method and construction method of fuzzy rule matrix. The method overcomes the disadvantages of traditional network performance prediction method, considered only a single time series, without considering the drawbacks of other variables and forecast variables correlation of. Simulation results show that, the model can efficiently predict the network connection rate, provides the theory basis and the new scheme for comprehensive prediction of network performance.

关 键 词：接通率预测 模糊时间序列 二元预测模型 3G网络性能 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]