Embedding urban planning objective by integrated artificial immune system and cellular automata

Xiaoping Liu, Xia Li, Xiaohu Zhang, Gangqiang Chen, Shaoying Li, Yimin Chen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Artificial Immune System can be used in pattern recognition and self-adaptive learning for its strong computing power such as immune recognition, clonal selection, immune learning and immune memory, which is quite suitable for studying the complex geographical progress. And CA is proved to be convenient and effective for studying complex system. As a result, model based on integrating AIS with CA was built to simulate the urban evolution and planning in this paper. As planning objective was embedded into AIS algorithm, antibody will gradually evolve towards which by changing the evolutionary variation mechanism. Then urban developing spatial pattern based on different planning scenarios can be simulated, which will supply decision support for urban and land use planning. This paper designed six different scenarios for city development, and used AIS-based CA model to simulate the Pearl River Delta's urban development (1988-2002) under different planning scenarios. It also compared the urban compactness under different simulation results: "City Center" and "City Center-Expressway" models incline to result in a more compact form of urban; On the other hand, "Town Center" and "Road" models come into being a relatively scattered and decentralized form of urban areas. Simulated results indicate that "City Center-Expressway" is the best development mode for the Pearl River Delta.

Original languageEnglish
Pages (from-to)882-894
Number of pages13
JournalDili Xuebao/Acta Geographica Sinica
Volume63
Issue number8
StatePublished - Aug 2008
Externally publishedYes

Keywords

  • Artificial immune system
  • Cellular automata
  • Pearl River Delta
  • Urban planning objective
  • Urban simulation

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