计算机科学 ›› 2009, Vol. 36 ›› Issue (12): 197-198.
• 人工智能 • 上一篇 下一篇
王媛妮,边馥苓
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WANG Yuan-ni,BIAN Fu-ling
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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。
关键词: 空间聚类,障碍约束,演化算法
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.
Key words: Spatial clustering, Obstacle constrain, Evolutionary algorithm
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. https://doi.org/
WANG Yuan-ni,BIAN Fu-ling. Clustering Based on Evolutionary Algorithm in the Presence of Obstacles[J]. Computer Science, 2009, 36(12): 197-198. https://doi.org/
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