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  • 标题:A Self-Adjusting Approach to Identify Hotspots
  • 本地全文:下载
  • 作者:Haoying Han ; Xianfan Shu
  • 期刊名称:International Review for Spatial Planning and Sustainable Development
  • 电子版ISSN:2187-3666
  • 出版年度:2017
  • 卷号:5
  • 期号:2
  • 页码:104-112
  • DOI:10.14246/irspsd.5.2_104
  • 语种:English
  • 出版社:空間計画と持続可能な開発国際学会
  • 摘要:Hotspot identification or detection has been widely used in many fields; however the traditional grid-based approaches may incur some problems when dealing with point database. This article expands on three types of mismatch problems in grid-based approach and suggests a point-based approach may be more suitable. Inspired by the DBSCAN algorithm, a self-adjusting approach is then proposed for hotspot detection which overcomes the weakness of parameter sensitivity shared by most clustering approaches. Finally, the data of commercial points of interest of a city is used for demonstration.
  • 关键词:Hotspot Detection;Self-adjusting Approach;Clustering;DBSCAN
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