协同演化算法在聚类中的应用

被引：4

作者：

董红斌 ^{[1
]}

杨宝迪 ^{[1
]}

刘佳媛 ^{[2
]}

侯薇 ^{[1
]}

机构：

[1] 哈尔滨工程大学计算机科学与技术学院

[2] 哈尔滨工程大学信息与通信工程学院

来源：

模式识别与人工智能 | 2012年 / 25卷 / 04期

基金：

黑龙江省自然科学基金;

关键词：

聚类; 模糊C均值(FCM); 遗传算法; 差分进化算法;

D O I：

10.16451/j.cnki.issn1003-6059.2012.04.012

中图分类号：

TP311.13 [];

学科分类号：

1201 ;

摘要：

提出一种协同演化聚类算法,该算法使用改进的掩码方式动态决定聚类中心的数目.将种群划分成两个子种群,分别采用遗传算法和差分进化算法进行演化,遗传算法侧重于全局寻优,差分进化算法注重于局部搜索.在演化的过程中,利用不同的间隔迁移策略相互交换优良个体,使算法的全局探索能力和局部搜索能力得到均衡.通过性能测试、聚类中心数目和运行时间测试等实验证明该算法的优越性.

引用

页码：676 / 683

页数：8

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