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Cluster Computing

, Volume 22, Supplement 6, pp 14827–14833 | Cite as

The application researches of visualized data mining technique in urban underground space based on GIS

  • Fayong Zhang
  • Caixian LiEmail author
  • Yunling Yang
Article
  • 103 Downloads

Abstract

This article conducted researches of city ground spatial data mining system based on GIS, including several critical algorithms, technologies, and design approaches. Breaking through GIS technology and spatial data model, it proposed a kind of support vector machines mining method which was based on CBR case study undertaking previews and space fields differentiation. By the simulation of comparing the machines’ learning time, this method, in a way, shortened the studying time of machines, and can improve spatial mining data efficiency with huge data volume. Besides, aimed for Spatial clustering analysis methods, it proposed that replacing statistical distance with Euclidean distance can decline the false differentiation effects which was brought by the data itself.

Keywords

SVM algorithm GIS Data mining 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Information EngineeringChina University of GeoSciencesWuhanChina
  2. 2.Assert Company, China University of GeoSciencesWuhanChina

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