Using Genetic Algorithms to Create Multicriteria Class Intervals for Choropleth Maps.

Details of the design, implementation, and evaluation of an innovative approach to classification for choropleth maps through the use of a genetic algorithm are presented. It is noted that such an approach to classification places class-interval selection in a multicriteria framework.

Detalles Bibliográficos
Publicado en:Annals of the Association of American Geographers Vol. 93; no. 3; pp. 595 - 624
Autores principales: Armstrong, Marc P., Xiao, Ningchuan, Bennett, David A.
Formato: Artículo
Publicado: Taylor & Francis Ltd September 2003
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=513148413&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 513148413
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00045608
        AAG
      jtl: Annals of the Association of American Geographers
      issn: 00045608
      maglogo: N
    pubinfo:
      dt: September 2003
      vid: 93
      iid: 3
      pid: 377
      pub: Taylor & Francis Ltd
    artinfo:
      ui:
        513148413
        10.1111/1467-8306.9303005
      ppf: 595
      ppct: 29
      formats:
      tig:
        atl: Using Genetic Algorithms to Create Multicriteria Class Intervals for Choropleth Maps.
      aug:
        au:
          Armstrong, Marc P.
          Xiao, Ningchuan
          Bennett, David A.
      su:
        Statistical maps
        Genetic algorithms
        Geography -- Methodology
        Geography -- Statistical methods
      sug:
        subj:
          Statistical maps
          Genetic algorithms
          Geography -- Methodology
          Geography -- Statistical methods
      ab: Details of the design, implementation, and evaluation of an innovative approach to classification for choropleth maps through the use of a genetic algorithm are presented. It is noted that such an approach to classification places class-interval selection in a multicriteria framework.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N