基于DPC 算法与模块密度的改进Chameleon 算法

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基于DPC 算法与模块密度的改进Chameleon 算法

宫峰勋^a，邢晨^a，马艳秋^b

（taptap下载安装安卓a.电子信息与自动化学院；b.科技处，天津300300）

收稿日期:2017-04-10 修回日期:2017-04-10 出版日期:2017-12-27 发布日期:2017-12-15
作者简介:宫峰勋（1965—），男，吉林九台人，教授，硕士，研究方向为通信与信息系统、民航通信导航监视及多源数据融合.
基金资助:
国家自然科学基金项目（U1533108，U1233112）

Improved Chameleon algorithm based on DPC algorithm and module density

GONG Fengxun^a, XING Chen^a, MA Yanqiu^b

(a. College of Electronic Information and Automation; b. Science and Technology Department, CAUC, Tianjin 300300, China)

Received:2017-04-10 Revised:2017-04-10 Online:2017-12-27 Published:2017-12-15

摘要/Abstract

摘要： 本研究基于Chameleon 算法结合DPC 算法和模块密度函数,提出一种基于密度的层次聚类算法。在Chameleon 算法第一阶段,引入DPC 算法进行数据处理,在第二阶段,利用近似度函数进行子簇合并时,引入表征簇内数据点相似程度的函数——模块密度,当模块密度值最大时获得最终聚类结果。本算法利用上述方法建立动态模型,可自动确定终止条件,并且可以识别任意形状簇,克服了传统Chameleon 算法无法找到聚类终点和对于初始参数设置敏感的问题。

关键词: Chameleon 算法, DPC 算法, 模块密度, 稳健性

Abstract: Based on Chameleon algorithm, DPC algorithm and mudule density function, a hierarchical clustering algorithm based on density is proposed. In the first stage of Chameleon algorithm, DPC algorithm is used for data processing. In the second stage, when clusters are merged with the approximation function, module density that characterizes the similarity of data within a cluster is introduced. When module density achieves maximum,termination condition and final clustering result are obtained. An improved Chameleon algorithm is used to establish dynamic model, which can automatically determine the termination condition, and can identify many shape clusters, helping traditional Chameleon algorithm find the clustering end and be less sensitive to the initial parameter setting.

Key words: Chameleon algorithm, DPC algorithm, module density, robustness

中图分类号:

TP391.4

宫峰勋，邢晨，马艳秋. 基于DPC 算法与模块密度的改进Chameleon 算法[J]. taptap下载安装安卓学报.

GONG Fengxun, XING Chen, MA Yanqiu. Improved Chameleon algorithm based on DPC algorithm and module density[J]. .