• DocumentCode
    3144320
  • Title

    An adaptive genetic algorithm based on rough set attribute reduction

  • Author

    Liu, BingXiang ; Liu, Feng ; Cheng, Xiang

  • Author_Institution
    Sch. of Inf. Eng., JDZ Ceramic Inst., Jingdezhen, China
  • Volume
    7
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    2880
  • Lastpage
    2883
  • Abstract
    Attribute reduction is one of important problem of rough set theory. In order to get effectively attribute reduction, we presented an algorithm of attribute reduction of rough set based on improved adaptive genetic algorithm (IAGA). IAGA adjusts the crossover probability and mutation probability of each individual according to individual fitness value. The optimization capability and the convergence velocity of adaptive GA are improved.
  • Keywords
    genetic algorithms; probability; rough set theory; GA; adaptive genetic algorithm; attribute reduction; crossover probability; mutation probability; rough set theory; Biological cells; Convergence; Encoding; Gallium; Genetic algorithms; Information systems; Set theory; Adaptive; Attribute reduction; Genetic Algorithm; Rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6495-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2010.5639635
  • Filename
    5639635
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3144320