计算机应用 ›› 2013, Vol. 33 ›› Issue (05): 1222-1229.DOI: 10.3724/SP.J.1087.2013.01222

• 网络与通信 • 上一篇    下一篇

改进模糊自回归模型在预测网络接通率中的应用

申晨,孙永雄,黄丽平,刘李蓬,李树秋   

  1. 吉林大学 计算机科学与技术学院,长春 130012
  • 收稿日期:2012-11-02 修回日期:2012-12-08 出版日期:2013-05-01 发布日期:2013-05-08
  • 通讯作者: 申晨
  • 作者简介:申晨(1988-),男,河北保定人,硕士研究生,主要研究方向:计算机通信;孙永雄(1970-),男,甘肃武威人,副教授,硕士,主要研究方向:计算机通信、医学图像处理;黄丽平(1988-),女,吉林辽源人,硕士研究生,主要研究方向:3G网络优化、医学图像处理;刘李蓬(1989-),男,吉林图门人,硕士研究生,主要研究方向:计算机通信、医学图像处理;李树秋(1966-),男,黑龙江尚志人,副教授,博士,主要研究方向:计算机网络与通信、嵌入式技术、计算机支持协同工作
  • 基金资助:

    吉林省重点科技发展项目(20120436,20100309);吉林省重点科技发展项目(20120436,20100309)

Improved fuzzy auto-regressive model for connection rate prediction

SHEN Chen,SUN Yongxiong,HUANG Liping,LIU Lipeng,LI Shuqiu   

  1. College of Computer Science and Technology, Jilin University, Changchun Jilin 130012, China
  • Received:2012-11-02 Revised:2012-12-08 Online:2013-05-08 Published:2013-05-01
  • Contact: SHEN Chen

摘要: 针对通信网络中性能指标预测的需要,提出了基于改进的模糊自回归模型的接通率预测方法,研究了拟合度门限自适应的模糊自回归模型。将中值滤波应用于模糊自回归模型的数据预处理中,在此基础上,针对部分应用拟合度门限不明确的特点,将拟合度门限计算式加入预测模型中,实现模型拟合度门限的自适应。仿真实验表明:基于Fuzzy AR模型的预测方法可以用于对接通率的预测,预测结果拟合度较高。

关键词: 模糊预测, 自适应拟合度, 模糊自回归模型, 接通率预测, 数据预处理

Abstract: Specific to the need of performance prediction in communication networks, a connection rate prediction method based on fuzzy Auto-Regressive (AR) model was proposed and improved, and the fuzzy AR model based on adaptive fitting degree threshold was studied. The median filtering method was applied to pre-process the data of fuzzy AR model. On this basis, for the uncertain thresholds of some applications, the fitting degree threshold formula was added to the prediction model to make it adaptive. The simulation results show that the predistion method based on fuzzy AR model can be used to predict the connection rate with a higher fitting degree.

Key words: fuzzy prediction, adaptive fitting degree, fuzzy Auto-Regressive (AR) model, connection rate prediction, data preprocessing

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