• DocumentCode
    480755
  • Title

    A Neural-Network-Based Geographic Tendency Visualization

  • Author

    Hotta, Hajime ; Hagiwara, Masafumi

  • Author_Institution
    Fac. of Sci. & Technol., Keio Univ., Yokohama
  • Volume
    1
  • fYear
    2008
  • fDate
    9-12 Dec. 2008
  • Firstpage
    817
  • Lastpage
    823
  • Abstract
    In this paper, we propose a neural-network-based visualization system of geographic tendency. In general, there are some needs of understanding statistical data of geographic tendency, such as geographic marketing data, real-estate prices, and so on. The main purpose of the proposal is to visualize the tendency of these data online with interactive mapping systems, such as Google Maps. The proposed system generates translucent images of a heatmap, which shows the geographic tendency like thermograph. It consists of two steps: (1) construction of a tendency model with a neural network, (2) determine the color scale for the output heatmap. As for (1), a general regression neural network (GRNN) is employed to compose a tendency model by function approximation. As for (2), the output color scale is optimized and the heatmap is finally generated using the composed tendency model.
  • Keywords
    cartography; data visualisation; function approximation; image colour analysis; interactive systems; neural nets; regression analysis; Google Map; color scale map; function approximation; general regression neural network; heatmap translucent image; neural-network-based geographic tendency visualization system; online interactive mapping system; thermograph; Intelligent agent; Visualization; geographic; neural network; visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-0-7695-3496-1
  • Type

    conf

  • DOI
    10.1109/WIIAT.2008.141
  • Filename
    4740556