| 基于蚁群聚类算法的离群挖掘方法 |
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| 引用本文： | 杨欣斌,孙京诰,黄道. 基于蚁群聚类算法的离群挖掘方法[J]. 计算机工程与应用, 2003, 39(9): 12-13,37 |
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| 作者姓名： | 杨欣斌 孙京诰 黄道 |
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| 作者单位： | 华东理工大学信息学院,上海,200237 |
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| 摘 要： | 离群挖掘是数据挖掘研究的重要内容,在实际生活中获得广泛应用。该文首先给出了离群数据的量化定义,并用基于蚁群的聚类学习方法,产生了状态空间的整体特征。然后结合具体的设备对象,提出了离群数据的挖掘方法。最后进行了实验验证,结果表明该文提出的方法是有效的。
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| 关 键 词： | 离群数据 数据挖掘 蚁群 聚类 |
| 文章编号： | 1002-8331-(2003)09-0012-02 |
Research on Fault Diagnosis Based on Outlier Mining |
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| Yang Xinbin Sun Jinggao Huang Dao. Research on Fault Diagnosis Based on Outlier Mining[J]. Computer Engineering and Applications, 2003, 39(9): 12-13,37 |
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| Authors: | Yang Xinbin Sun Jinggao Huang Dao |
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| Abstract: | Outlier mining is an important issue in data mining community.It was applied widely in practice.A quantitative definition is proposed at the beginning of this paper.The integral character of the state space is created using the clustering method based on ant colony.And a method of mining outlier is put forward according to the practical device.At the end,an experiment has been done and the result proves the effectiveness of the method. |
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| Keywords: | outlier mining data mining ant colony clustering |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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