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  • 标题:Parametric clustering of cities
  • 本地全文:下载
  • 作者:Nataliya Muromtseva ; Tatiana Simankina ; Irina Alpackaya
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2020
  • 卷号:164
  • 页码:1-6
  • DOI:10.1051/e3sconf/202016404005
  • 出版社:EDP Sciences
  • 摘要:The article analyzes the master plans and functional areas of 42 cities from different federal districts of the Russian Federation. To identify the dependencies between the characteristics of localities and the allocation of functional zones in them, the data clustering method was applied. Also criteria for clustering were identified – these are quantitative characteristics that are universal for various localities: total area of a locality, population, population density and gross regional product. With these criteria clustering was carried out using the software package «Deductor», based on algorithms of neural network modeling. Self-organizing Kohonen maps (SOM) were used to visualize the obtained data. As a result of the clustering the connection between the characteristics of localities and the ratio of functional zones in them is revealed.
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