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Proceedings Paper

A improved particle swarm optimization based on cloud model with implications for urban land use planning
Author(s): Yanfei Wei; Yaolin Liu; Dun Wang
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Paper Abstract

In order to solve the dependence on the problem of patch technology in the constrained optimization of Particle Swarm Optimization (PSO), conversion will be achieved on the qualitative and quantitative of feasibility rules of the PSO algorithm by the uncertain illation and figure characteristics of cloud .The quantification of binding correction factor will be done in order to realize the common patch methods of different issues. The improved algorithm will be applied to the urban land use planning of Nanning and Yulin city in Guangxi. Quantifying the land conversion factor and combining with spatial analyses technology, analyzing and contrasting the land conversion area of the two cities, this improved algorithm will be proved to settle different problems.

Paper Details

Date Published: 16 October 2009
PDF: 7 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74923T (16 October 2009); doi: 10.1117/12.838390
Show Author Affiliations
Yanfei Wei, Wuhan Univ. (China)
Guangxi Teachers Education Univ. (China)
Yaolin Liu, Wuhan Univ. (China)
Dun Wang, Wuhan Univ. (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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