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Proceedings Paper

An adaptive grid algorithm for 3-D GIS landform optimization based on improved ant algorithm
Author(s): Chenhan Wu; Lingkui Meng; Shijun Deng
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Paper Abstract

The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ▵τj to ▵τji and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.

Paper Details

Date Published: 31 July 2006
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59601D (31 July 2006); doi: 10.1117/12.631401
Show Author Affiliations
Chenhan Wu, Wuhan Univ. (China)
Lingkui Meng, Wuhan Univ. (China)
Shijun Deng, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005

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