• DocumentCode
    2118601
  • Title

    Preliminary study on cluster methods for geometric shape based on correlation graph

  • Author

    Wang, Wei ; Quan, Cong ; He, Jin ; Wang, Xinsheng

  • Author_Institution
    Fac. of Resources & Environ. Sci., Hubei Univ., Wuhan, China
  • fYear
    2012
  • fDate
    21-23 April 2012
  • Firstpage
    2757
  • Lastpage
    2760
  • Abstract
    On study for geographic information science, description and measurement for shape of spatial objects is a very important research subject. But current methods used in this field all have some limitations. In this paper the authors discuss a new method to solve the problem better. The authors also put forward a new association matrix-Angular Matrix, which can represent geometric shape in a better way. Preliminary experiment shows that this method can express characteristics of geometric shape better with desirable calculation efficiency.
  • Keywords
    computational geometry; geographic information systems; graph theory; matrix algebra; pattern clustering; angular matrix; association matrix; cluster methods; correlation graph; geographic information description; geographic information science; geometric shape; spatial objects; Correlation; Laplace equations; Shape; Shape measurement; Symmetric matrices; Vectors; Angular Matrix; Association Matrix; Clustering Analysis; Delaunay Triangulation Network; Geometric Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4577-1414-6
  • Type

    conf

  • DOI
    10.1109/CECNet.2012.6201693
  • Filename
    6201693