Automatic terrain selection based on clustering and genetic algorithm

Quan Xin Zhang*, Jian Jun Zheng, Hai Yun Ling, Xiu Mei Fan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Terrain selection can't be realized automatically in C3I. For a certain GIS, an automatic terrain selection based on clustering (CTS) is proposed. It processes the data from the DEM layer according to constrained conditions, and constructs clusters by unconnected graph traversal in order to obtain the primary terrain. Another terrain selection based on genetic algorithm (GATS) is also proposed. It uses correlative selection operator in the family, adjusts dynamically crossover and mutation ratios, and designs fitness function by utilizing synthetically several species of constrained conditions and fuzzy membership degree so as to optimize terrain selection. Wherein, CTS doesn't need to assign the numbers of clusters previously, and the selected terrain accord with primary requirement. GATS can provide prepared multi-schemes straightway. The experimental results show that the two methods are feasible and effective.

Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Pages372-376
Number of pages5
DOIs
Publication statusPublished - 2007
Event6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 - Hong Kong, China
Duration: 19 Aug 200722 Aug 2007

Publication series

NameProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Volume1

Conference

Conference6th International Conference on Machine Learning and Cybernetics, ICMLC 2007
Country/TerritoryChina
CityHong Kong
Period19/08/0722/08/07

Keywords

  • Clustering
  • GIS
  • Genetic algorithm
  • Terrain selection

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