| 模糊C-均值聚类算法改进研究 |
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| 引用本文： | 刘颖,胡智鹏.模糊C-均值聚类算法改进研究[J].吉林化工学院学报,2012,29(11):124-126. |
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| 作者姓名： | 刘颖 胡智鹏 |
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| 作者单位： | 北华大学信息技术学院,吉林吉林,132013 |
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| 摘 要： | 通过对模糊C-均值聚类算法的研究,用遗传算法的相关知识对其进行优化与改进.并使用著名的IRIS数据集分别对传统的模糊C-均值聚类算法和用遗传算法改进后的模糊C-均值聚类算法进行测试、比较.实验结果表明,用遗传算法改进后的模糊C-均值聚类算法比传统的模糊C-均值聚类算法更加准确、高效.这将为以后的聚类分析研究工作提供一定的帮助.
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| 关 键 词： | 聚类分析 FCM 模糊C-均值聚类 遗传算法 聚类有效性 |
The Improvement and Research of Fuzzy C-Means Clustering Algorithm |
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| LIU Ying,HU Zhi-peng.The Improvement and Research of Fuzzy C-Means Clustering Algorithm[J].Journal of Jilin Institute of Chemical Technology,2012,29(11):124-126. |
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| Authors: | LIU Ying HU Zhi-peng |
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| Affiliation: | (College of Information Technology,BeiHua University,Jilin City 132013,China) |
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| Abstract: | It is optimized and improved with the related knowledge of genetic algorithm through the research on the c-means clustering algorithm.The famous IRIS data is used to respectively test and compare the traditional c-means clustering algorithm and the c-means clustering algorithm improved by genetic algorithm.The results show that the c-means clustering algorithm improved by genetic algorithm is more accurate and efficient than traditional c-means clustering algorithm.Which provides some help for the future research work of clustering analysis. |
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| Keywords: | clustering analysis FCM Fuzzy C-means genetic algorithm clustering validity |
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