| QPSO与K-Medoids相结合的带障碍空间聚类新算法 |
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| 引用本文： | 杨腾飞,张雪萍,刘亚威.QPSO与K-Medoids相结合的带障碍空间聚类新算法[J].电子设计工程,2011,19(2):74-77,80. |
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| 作者姓名： | 杨腾飞 张雪萍 刘亚威 |
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| 作者单位： | 1. 河南工业大学,信息科学与工程学院,河南,郑州,450001
2. 河南工业大学,信息科学与工程学院,河南,郑州,450001;空间数据挖掘与信息共享教育部重点实验室,福建,福州,350002 |
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| 基金项目： | 教育部新世纪优秀人才支持计划，空间数据挖掘与信息共享教育部重点实验室开放基金，河南省高校科技创新人才支持计划，河南省科技攻关项目，郑州市科技攻关项目，河南工业大学高层次人才基金 |
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| 摘 要： | 分析了现有的带障碍约束空间聚类算法,针对基于PSO优化的带障碍约束的K-Me足,提出了QPSO与K-Medoids算法结合的带障碍空间聚类新算法(QKSCO).在带障碍约束的空间条件下,该算法依据蚁群格网障碍距离作为聚类依据,引入了QPSO的快速全局收敛的特性,使之与K-Medoids算法的局部收敛特性相得益彰.实验结...
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| 关 键 词： | 空间聚类 障碍约束 K-Medoids算法 QPSO算法 |
Spatial clustering algorithm with obstacles constraints by QPSO and K-Medoids |
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| YANG Teng-fei,ZHANG Xue-ping,LIU Ya-wei.Spatial clustering algorithm with obstacles constraints by QPSO and K-Medoids[J].Electronic Design Engineering,2011,19(2):74-77,80. |
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| Authors: | YANG Teng-fei ZHANG Xue-ping LIU Ya-wei |
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| Affiliation: | 1(1.School of Information Science and Engineering,Henan University of Technology,Zhengzhou 450001,China; 2.Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education,Fuzhou 350002,China) |
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| Abstract: | The paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-Medoids named QKSCO in allusion to the disadvantage of the spatial clustering algorithm with obstacles constraints by PSO and K-Medoids,based on the analysis of the existing algorithms of spatial clustering with obstacles constraints.In the space with obstacles constraints,this algorithm used the distance with obstacle to clustering,and introduced QPSO’s rapid global convergence to complement the local convergence of K-Medoids algorithm.The experimental results indicated that the new algorithm is more stable than the spatial clustering algorithm with obstacles constrains by particle swarm optimization and K-Medoids,and has better clustering results. |
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| Keywords: | spatial clustering obstacle constraints K-Medoids Quantum Particle Swarm Optimization |
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