Abstract
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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Yang, X., Yang, W., Zeng, M., Shi, Y. (2004). A Novel Network Traffic Analysis Method Based on Fuzzy Association Rules. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2004. Lecture Notes in Computer Science(), vol 3131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27774-3_9
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DOI: https://doi.org/10.1007/978-3-540-27774-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22555-3
Online ISBN: 978-3-540-27774-3
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