Feature Weighted and Improved Partition Fuzzy C-Means Cluster Algorithm

XIAO Lin-yun; CHEN Xiu-hong; LIN Xi-lan

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Feature Weighted and Improved Partition Fuzzy C-Means Cluster Algorithm

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- Feature Weighted and Improved Partition Fuzzy C-Means Cluster Algorithm
- Vol. 33, Issue 10, Pages: 143-146(2016)
- 作者机构：
  
  江南大学数字媒体学院,江苏,无锡,214122
- 作者简介：
- 基金信息：
- DOI：
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- Published：2016
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肖林云, 陈秀宏, 林喜兰. 特征加权和优化划分的模糊C均值聚类算法[J]. 微电子学与计算机, 2016, 33(10): 143-146, 150.

XIAO Lin-yun, CHEN Xiu-hong, LIN Xi-lan. Feature Weighted and Improved Partition Fuzzy C-Means Cluster Algorithm[J]. 2016, 33(10): 143-146.
肖林云, 陈秀宏, 林喜兰. 特征加权和优化划分的模糊C均值聚类算法[J]. 微电子学与计算机, 2016, 33(10): 143-146, 150. DOI：

XIAO Lin-yun, CHEN Xiu-hong, LIN Xi-lan. Feature Weighted and Improved Partition Fuzzy C-Means Cluster Algorithm[J]. 2016, 33(10): 143-146. DOI：

摘要

在传统FCM算法基础上提出一种称为特征加权和优化划分的模糊C均值算法(WGIFP-FCM).该算法结合了优化划分法和特征权重思想

得到特征权重向量迭代公式并在聚类处理过程中自适应地更新.仿真实验结果表明

该算法能科学地计算出样本特征权重向量

获得优于GIFP-FCM、WFCM和FCM的聚类效果

具有一定实际应用价值.

Abstract

This paper proposes a new algorithm based on the FCM

which is called feature weighting and optimal fuzzy partition of fuzzy c-means algorithm (WGIFP - FCM). This algorithm combines the optimization partition method and the feature weight idea

obtains feature weight vector formula and updates it in the entire clustering process.Simulation experiments have proved that the proposed algorithm has gotten better clustering results than GIFP - FCM

WFCM and FCM while calculating the weighting vector scientifically

and so it will be available in practice.

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references

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朱红霞, 王黎明. 改进的自适应模糊C均值聚类图像分割算法[J]. 微电子学与计算机, 2010, 27(12): 87-89. DOI: 87

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