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Proceedings Paper

An improved Voronoi diagram model based on fuzzy interval theory
Author(s): Beibei Yan; Zhenfeng Shao; Yang Zhou; Qimin Cheng
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Paper Abstract

Considering that the application of traditional Voronoi diagram in spatial division ignores the impact of road hierarchy, speed, road-block, one-way and some other influential factors on proximity, an improved Voronoi diagram model based on fuzzy interval theory is proposed in this paper by introducing different influential factors into the construction of Voronoi diagram in order to enhance the accuracy of spatial division and to meet application requirements. The idea of our improved Voronoi diagram model can be summarized as follows: Firstly, initial Voronoi diagram is built via point by point insertion algorithm. Secondly, fuzzy interval on all Voronoi edges is generated via geometric algorithm and is further used to represent each edge of Voronoi polygons. The size of fuzzy interval is determined by taking all influential factors into consideration. Thirdly, an improved Voronoi diagram with fuzzy boundaries is provided in which the proximity relationships between points in the fuzzy interval and the sites of Voronoi polygons which own a public edge are all proposed to be the nearest. Finally, the validity and performance of our improved Voronoi diagram is demonstrated through a typical application in emergency response system, in which the actual path distance is acted as influential factor. Experimental results show that with our improved Voronoi diagram optimal attendance station can be localized quickly and emergency response efficiency can be enhanced obviously. Besides, classification accuracy can be increased more than 20% compared with traditional Voronoi diagram.

Paper Details

Date Published: 16 October 2009
PDF: 9 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74924N (16 October 2009); doi: 10.1117/12.838273
Show Author Affiliations
Beibei Yan, Wuhan Univ. (China)
Zhenfeng Shao, Wuhan Univ. (China)
Yang Zhou, Wuhan Univ. (China)
Qimin Cheng, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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