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Spatial analysis for functional region of suburban-rural area using micro genetic algorithm with variable population size

  • Yi Chen
  • , Zhi Jun Song*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

A micro genetic algorithm with variable population size (VPμGA) is proposed for the spatial analysis for the functional region of suburan-rural area, in which, the fitness function is implied by a functional region affecting index (Θ) with a 'law-of-gravity' interpretation. The VPμGA evaluates the Θ represented dynamical behaviours over a 'short' to 'long' term period, which also revisits the urbanisation of Beijing and examines the Θ sensitivity to the functional distance of 13 suburban-rural districts. Numerical results with given statistics has been obtained using a specially devised simulation toolkit, it is shown that the VPμGA method can work valuably as a tool for providing a functional distanced based estimation of the inter-relationships between the enterprises number, the regional profit, the local population, the regional employment, etc.; and to use this understanding to evaluate suburban-rural districts that are more resilient and adaptable.

Original languageEnglish
Pages (from-to)6469-6475
Number of pages7
JournalExpert Systems with Applications
Volume39
Issue number7
DOIs
StatePublished - 1 Jun 2012
Externally publishedYes

Keywords

  • Functional region
  • Genetic algorithms
  • Micro genetic algorithm
  • Rural area
  • Spatial analysis
  • Suburban area

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

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