Study and application of a novel method of outlier mining

被引：0
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作者：
CIMS Center, Tongji University, Shanghai 200092, China [1 ]
不详 [2 ]
不详 [3 ]
机构：
来源：
Kongzhi yu Juece Control Decis | 2006年 / 5卷 / 563-566+571期
关键词：
Algorithms - Applications - Data processing - Equipment - Industry;
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学科分类号：
摘要：
Outlier mining is an important part of data mining. Combining ant colony algorithm with k-means algorithm, excellent results of clustering analysis are obtained. Then, a novel measure for identifying the physical significance of an outlier is designed by some permanents of ant colony algorithm and k-means algorithm, which is called cluster-based outlier index. The Find Ant_CO(t) algorithm for discovering outliers is proposed. Based on the models, the equipment process is optimized and the faults are monitored.
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