An Algorithm of Multi-Level Fuzzy Association Rules Mining With Multiple Minimum Supports in Network Faults Diagnosis

被引:0
|
作者
Liu, Pan [1 ]
Li, Xing-ming [1 ]
Feng, Yan-qing [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Commun & Informat Engn, Chengdu 610054, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu, Peoples R China
关键词
Network Fault Management; Alarm Correlation Analysis; Multi-Level Network; Fuzzy Association Rules Mining;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The alarm correlation analysis based on multi-level fuzzy association rules mining is the cutting-edge field of the network fault diagnosis research. In the application environment of alarms in communication networks, multi-level fuzzy association rules mining algorithms are proposed, and two strategies are adopted to set minimum support, which are multiple minimum supports and one minimum support. Simulations are carried out to the comparison of algorithms under the two strategies. Multi-level fuzzy association rules mining of alarms is effectively realized. The advantages and efficiency of algorithms are demonstrated by the experiments.
引用
收藏
页码:884 / 888
页数:5
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