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基于路径的聚类分析 被引量:3

Automatic Clustering of Point-Data Sets Based on Path
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摘要 聚类分析的很多算法中都采用连接两点直线的欧氏距离来判断空间亲疏性,然而当有障碍物层存在时,连接两点的直线已不能完全表达它们之间的关系,特别是当有指定的交通路线时,两点之间的连通路径和距离必须遵从特定的路径。文中讨论在了障碍物或指定的交通路线存在的情况下点集的聚类分析,给出了解决有障碍物或指定交通路线时进行聚类分析的算法PathClust。 Many clustering algorithms use the Euclidean However, when the layers of obstacles presented, the tions completely. Especially, when the transportation trace the some fixed path. PathClust is put forward to distance of two points to measure the spatial proximity, line linking the two points could not represent the rela network exists, the route linking the two points must realize the clustering of points in the presence of obstacles or the transportation networks.
出处 《测绘科学技术学报》 北大核心 2006年第2期145-148,共4页 Journal of Geomatics Science and Technology
关键词 聚类分析 地址匹配 最佳路径 最佳距离 clustering analysis address geoeoding optimum route the shortest distance
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参考文献4

  • 1[1]Estivill-Castro V,Lee I AUTOCLUST.Automatic Clustering via Boundary Extraction for Massive Points-data Sets[A].Proceedings of the 5th International Conference on Geo-computation[C],2000.
  • 2[2]Goochild M F.Geographical Information Science[J].International Journal of Geographical Information Systems,1992,6(1):31-45.
  • 3[3]Kang I,Kim T,Li K.A Spatial Data Mining Methods By Delaunay Triangulation[A].Proceedings of the 5th International Workshop on Advances in Geographic Information Systems (GIS-97)[C],1997:35-39.
  • 4[4]Eldershaw C,Hegland M.Clustering Analysis using Triangulation.Computational Techniques and Applications[A].CTAC97[C].Singapore:World Scientific,1997:201-208.

同被引文献19

  • 1李娜,杜清运,吴小芳,蔡忠亮,周梅玫.制图综合中道路与建筑物的移位研究[J].测绘科学,2006,31(4):92-94. 被引量:6
  • 2陈继东,孟小峰,赖彩凤.基于道路网络的对象聚类[J].软件学报,2007,18(2):332-344. 被引量:29
  • 3V Estivill-Castro and I Lee. AUTOCLUST: Automatic Clustering via Boundary Extraction for Massive Points-data Sets[C] //Proceedings of the 5^th International Conference on Geo-computation. 2000.
  • 4I Kang , T Kim, and K Li. A Spatial Data Mining Methods By Delaunay Triangulation [ C ] //In Proceedings of the 5^th International Worksho Pon Advances in Geographic Information Systems (GIS-97) . 35-39, 1997.
  • 5C Eldershaw and M Hegland. Clustering Analysis using Triangulation [ J ]. Computational Techniques and Ap- plications1997 : CTAC97. 201-208. World Scientific, Singapore.
  • 6M F Goochild. Geographical Information Science [J]. International Journal of Geographical Information Systems1992. 6(1) : 31-45.
  • 7V Estivill-Castro, I Lee. AUTOCLUST: Automatic Clus- tering via Boundary Extraction for Massive Points-data Sets [ C ]//Proceedings of the 5'h International Conference on Geo-computation. Chicago, 2000.
  • 8C Eldershaw, M Hegland. Clustering Analysis using Tri- angulation. Computational Techniques and Applications: CTAC97, 201-208[Z]. World Scientific, Singapore,1997.
  • 9M F Goochild. Geographical Information Science[J]. In- ternational Journal of Geographical Information Systems, 1992, 6 (1) :31-45.
  • 10刘贤腾.空间可达性研究综述[J].城市交通,2007,5(6):36-43. 被引量:142

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