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
Link To Document