Reducing Building Conflicts in Map Generalization with an Improved PSO AlgorithmReportar como inadecuado


Reducing Building Conflicts in Map Generalization with an Improved PSO Algorithm


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1

School of Resources and Environmental Science, Wuhan University, Wuhan 430079, China

2

Wuhan Geomatics Institute, Wuhan 430079, China

3

School of Geosciences, Yangtze University, Wuhan 430079, China





*

Author to whom correspondence should be addressed.



Academic Editors: Shih-Lung Shaw, Qingquan Li, Yang Yue and Wolfgang Kainz

Abstract In map generalization, road symbolization and map scale reduction may create spatial conflicts between roads and neighboring buildings. To resolve these conflicts, cartographers often displace the buildings. However, because such displacement sometimes produces secondary spatial conflicts, it is necessary to solve the spatial conflicts iteratively. In this paper, we apply the immune genetic algorithm IGA and improved particle swarm optimization PSO to building displacement to solve conflicts. The dual-inheritance framework from the cultural algorithm is adopted in the PSO algorithm to optimize the topologic structure of particles. We generate Pareto optimal displacement solutions using the niche Pareto competition mechanism. The results of experiments comparing IGA and the improved PSO show that the improved PSO outperforms IGA; the improved PSO results in fewer graphic conflicts and smaller movements that better satisfy the movement precision requirements. View Full-Text

Keywords: graphic conflicts; displacement; PSO algorithm graphic conflicts; displacement; PSO algorithm





Autor: Hesheng Huang 1, Qingsheng Guo 1,* , Yageng Sun 2 and Yuangang Liu 3

Fuente: http://mdpi.com/



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