| 求解聚类问题的混合粒子群优化算法 |
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| 引用本文： | 高尚[,] 杨静宇.求解聚类问题的混合粒子群优化算法[J].科学技术与工程,2005,5(23):1792-1795. |
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| 作者姓名： | 高尚[ ] 杨静宇 |
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| 作者单位： | 1. 江苏科技大学电子信息学院,镇江,212003;南京理工大学计算机科学与技术系,南京,210094
2. 南京理工大学计算机科学与技术系,南京,210094 |
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| 摘 要： | 建立了聚类分析问题模型,结合遗传算法的思想提出的混合粒子群算法来解决聚类问题。该算法可 进一步改进,思路是利用K-均值方法的结果作为一个粒子。经过比较测试,4种粒子群算法的效果都比较 好,特别是交叉策略A和变异策略B的组合算法最好。
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| 关 键 词： | 粒子群 聚类问题 优化 |
| 文章编号： | 1671-1815(2005)23-1792-04 |
| 收稿时间： | 08 24 2005 12:00AM |
| 修稿时间： | 2005年8月24日 |
Solving Clustering Problem by Hybrid Particle Swarm Optimization Algorithm |
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| GAO Shang,YANG Jingyu.Solving Clustering Problem by Hybrid Particle Swarm Optimization Algorithm[J].Science Technology and Engineering,2005,5(23):1792-1795. |
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| Authors: | GAO Shang YANG Jingyu |
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| Institution: | School of Electronics and Information, Jiangsu University of Science and Technology 1 , Zhenjiang 212003; Department of Computer Science and Technology, Nanjing University of Science and Technology 2 , Nanjing 210094 |
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| Abstract: | An optimization mathematical model of clustering problem is given. The hybrid particle swarm optimization algorithm combine the ideal of the genetic algorithm is recommended to solve clustering problem. The algorithm is then extended to use K-means clustering to seed the initial swarm. All the 4 particle swarm optimization algorithms are proved effective. Especially the particle swarm optimization algorithm with across strategy A and mutation strategy B is a simple and effective better algorithm than others. |
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| Keywords: | particle swarm clustering problem optimization |
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