| 基于演化算法的带故障约束空间聚类分析 |
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| 引用本文： | 王媛妮,边馥苓.基于演化算法的带故障约束空间聚类分析[J].计算机科学,2009,36(12):197-198. |
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| 作者姓名： | 王媛妮 边馥苓 |
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| 作者单位： | 1. 武汉大学空间信息与数字工程研究中心,武汉,430079;中国地质大学计算机学院,武汉,430074
2. 武汉大学空间信息与数字工程研究中心,武汉,430079 |
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| 摘 要： | 现实世界当中的各种约束条件限制了空间聚类必须考虑这些限制条件的存在.主要研究带障碍物的空间聚类,采用K-中心点算法进行聚类分析,在解决空间对象绕过障碍物的最短距离时引进改进的郭涛算法进行求解,对于中小规模数据体现了较高的执行效率.通过理论分析和实验验证,该算法是可行的.
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| 关 键 词： | 空间聚类 障碍约束 演化算法 |
| 收稿时间： | 2009/3/14 0:00:00 |
| 修稿时间： | 6/1/2009 12:00:00 AM |
Clustering Based on Evolutionary Algorithm in the Presence of Obstacles |
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| WANG Yuan-ni,BIAN Fu-ling.Clustering Based on Evolutionary Algorithm in the Presence of Obstacles[J].Computer Science,2009,36(12):197-198. |
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| Authors: | WANG Yuan-ni BIAN Fu-ling |
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| Affiliation: | (Research Center of Spatial Information & Digital Engineering, Wuhan University, Wuhan 430079 , China);College of Computer,China University of Geosciences,Wuhan 430074,China) |
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| Abstract: | In the real-world, constraints limits the spatial clustering must take into account the conditions of these restrictions, this paper studied the spatial clustering with obstacles. It mainly used the K-medoid algorithm to cluster, and it introduced an improved algorithm Guo Tao to solve the distance of spatial objects in the presence of obstacles. It is higher efficiency for small and medium-sized data. Through theoretical analysis and experimental, the algorithm is feasible. |
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| Keywords: | Spatial clustering Obstacle constrain Evolutionary algorithm |
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