Study and application of a novel method of outlier mining

被引：0

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;

D O I：

暂无

中图分类号：

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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