A Novel Network Traffic Analysis Method Based on Fuzzy Association Rules

  • Xinyu Yang
  • Wenjing Yang
  • Ming Zeng
  • Yi Shi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3131)


For network traffic analysis and forecasting, a novel method based on fuzzy association rules is proposed in this paper. Connecting fuzzy logic theory with association rules, the method sets up the fuzzy association rules and could analyze the traffic of the global network by using data mining algorithm. Therefore, this method can represent the traffic’s characters much more precisely and forecast the behaviors of traffic in advance. The paper firstly introduces the new classification method on network traffic. Then the fuzzy association rules are applied to analyze the behaviors of traffic in existence. Finally, the results of simulation experiments indicating that the fuzzy association rule is very effective in discovering the relativity of different traffic in the analysis of traffic flow are shown.


Membership Function Association Rule Traffic Flow Network Traffic Membership Degree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Xinyu Yang
    • 1
  • Wenjing Yang
    • 1
  • Ming Zeng
    • 1
  • Yi Shi
    • 1
  1. 1.Dept. of Computer Science and TechnologyXi an Jiaotong UniversityXi anChina

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