Improved Clustering Algorithm Based on Cuckoo Search

SUN Wei-peng; MENG bin; WU Xi-sheng

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Improved Clustering Algorithm Based on Cuckoo Search

更新时间：2026-09-04

- Improved Clustering Algorithm Based on Cuckoo Search
- Vol. 35, Issue 8, Pages: 16-20(2018)
- 作者机构：
  
  1. 江南大学物联网工程学院,江苏,无锡,214122
  2. 中船重工集团第七〇二研究所软件工程中心,江苏,无锡,214082
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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孙伟鹏, 孟斌, 吴锡生. 基于布谷鸟搜索改进的聚类算法[J]. 微电子学与计算机, 2018, 35(8): 16-20.

SUN Wei-peng, MENG bin, WU Xi-sheng. Improved Clustering Algorithm Based on Cuckoo Search[J]. 2018, 35(8): 16-20.
孙伟鹏, 孟斌, 吴锡生. 基于布谷鸟搜索改进的聚类算法[J]. 微电子学与计算机, 2018, 35(8): 16-20. DOI：

SUN Wei-peng, MENG bin, WU Xi-sheng. Improved Clustering Algorithm Based on Cuckoo Search[J]. 2018, 35(8): 16-20. DOI：

摘要

在分析K-均值算法和布谷鸟搜索(CS)算法的基础上

本文提出了一种基于改进布谷鸟搜索算法的聚类算法.该算法将局部搜索能力强的K-均值算法和全局搜索能力强的布谷鸟搜索算法相结合.既提高了布谷鸟搜索算法的局部搜索能力

加快了收敛速度.同时因为布谷鸟搜索算法具有较强的全局搜索能力

有效地防止了早熟收敛现象的发生

因此可以有效地获得全局最优解.实验表明该聚类算法有更好的收敛效果.

Abstract

Based on the analysis of K-means algorithm and cuckoo search (CS) algorithm

this paper proposes a clustering algorithm based on improved cuckoo search algorithm. The algorithm combines the strong local search ability provided by K-means algorithm with the strong global search ability provided by improved cuckoo search algorithm. Which not only improves the local search ability of the cuckoo search algorithm

but also accelerates the convergence rate. At the same time

because the cuckoo search algorithm has strong global search ability

it can effectively prevent the premature convergence phenomenon

so it can effectively achieve the global optimal result. Experiments show that the clustering algorithm has a better convergence effect.

关键词

Keywords

references

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