• DocumentCode
    2917240
  • Title

    Genetic Algorithm-based ecosystem for heather management

  • Author

    Jin, Nanlin

  • Author_Institution
    Univ. of Leeds, Leeds
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    3282
  • Lastpage
    3288
  • Abstract
    This paper applies genetic algorithms (GA) to simulate a heather moorland ecosystem. We investigate, in this ecosystem how to manage heather for the benefits of survival and reproduction of grouse. A GA candidate solution is a grid, representing spatial relationship of three types of heather. From solutions provided by GA, we have found that the diversity of neighborhood and its distribution are essential. The evenly diversified heather distributions emerge as the best fit solutions for grousepsilas needs. We compared this finding with data collected from the field work.
  • Keywords
    ecology; genetic algorithms; data collection; genetic algorithm-based ecosystem; grouse; heather distributions; heather management; heather moorland ecosystem; spatial relationship; DC generators; Ecosystems; Evolutionary computation; Genetics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631242
  • Filename
    4631242