| 基于网格和密度权值的模糊c均值聚类算法 |
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| 引用本文： | 邱保志,卢海艇.基于网格和密度权值的模糊c均值聚类算法[J].计算机工程与设计,2010,31(4). |
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| 作者姓名： | 邱保志 卢海艇 |
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| 作者单位： | 郑州大学信息工程学院,河南,郑州,450001 |
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| 基金项目： | 国家自然科学基金项目 |
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| 摘 要： | 改进了基于网格和密度的模糊c均值聚类初始化方法,提出了基于网格和密度权值的模糊c均值算法.该算法在参数初始化时用网格代表点代替原算法的网格凝聚点,同时考虑到在样本空间中处于不同位置的样本点对聚类的影响不同,把密度权值作为系数加入到模糊c均值聚类算法中.实验结果表明,提出的算法对提高算法的效率是有效的.
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| 关 键 词： | 模糊C均值聚类算法 代表点 密度权值 |
Fuzzy c-means algorithm based on grid and density weight |
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| QIU Bao-zhi,LU Hai-ting.Fuzzy c-means algorithm based on grid and density weight[J].Computer Engineering and Design,2010,31(4). |
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| Authors: | QIU Bao-zhi LU Hai-ting |
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| Affiliation: | QIU Bao-zhi,LU Hai-ting(College of Information Engineering,Zhengzhou University,Zhengzhou 450001,China) |
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| Abstract: | An initialization method for fuzzy c-means clustering algorithm based on grid and density is improved,a new algorithm is presented.This algorithm is fuzzy c-means algorithm based on the grid and density weight(shorted for GDWFCM).GDWFCM uses the representative point in stead of the condensation point of grid;at the same time,taking into the account the fact that the sample point in different place will have different influence on the clustering results,we add the density weight as a coefficient to the fuzzy... |
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| Keywords: | GDWFCM GDFCM fuzzy c-means clustering algorithm representative point density weight GGWFCM GDFCM |
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