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[ "高会生,男,博士,华北电力大学电子与通信工程系教授、系主任,主要研究方向为电力系统通信。" ]
[ "李英敏,女,华北电力大学电子与通信工程系硕士生,主要研究方向为电力通信专网告警关联。" ]
网络出版日期:2014-10,
纸质出版日期:2014-10-20
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高会生, 李英敏. 基于综合相关置信度的告警关联规则挖掘[J]. 电信科学, 2014,30(10):110-115.
Huisheng Gao, Yingmin Li. Mining Alarm Association Rules Based on Comprehensive Related Confidence[J]. Telecommunications science, 2014, 30(10): 110-115.
高会生, 李英敏. 基于综合相关置信度的告警关联规则挖掘[J]. 电信科学, 2014,30(10):110-115. DOI: 10.3969/j.issn.1000-0801.2014.10.017.
Huisheng Gao, Yingmin Li. Mining Alarm Association Rules Based on Comprehensive Related Confidence[J]. Telecommunications science, 2014, 30(10): 110-115. DOI: 10.3969/j.issn.1000-0801.2014.10.017.
采用置信度融合算法计算相邻告警的综合相关置信度,并根据计算结果形成告警关联事务,增强告警事务内告警之间的相关性,降低对支持度的选择要求,有效挖掘出“低支持度-置信度”告警关联规则。利用h-置信度理论筛选有意义的告警关联规则,并通过实验比较了传统方法和本文方法的执行效率和挖掘正确率。
The traditional association rules mining algorithms preferred to applying single sliding time window
and the mined alarm association rules were high support-high confidence. To solve this problem
a method was proposed to calculate comprehensive related confidence between the time adjacent items by the confidence fusion algorithm. Then generated alarm transactions were generated based on the calculated results
which enhanced alarm correlation within a transaction. The proposed approach can reduce the choice of support requirement and mine low support-high confidence association rules effectively. Based on h-confidence theory
interesting alarm association rules were screened. Experimental results showed the feasibility and effectiveness of this approach.
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