• DocumentCode
    1901101
  • Title

    Case Retrieval Strategy Based on GAs and Group Decision-Making Method

  • Author

    Jiang, Wei ; Yan, Ai-jun ; Wang, Pu

  • Author_Institution
    Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Case retrieval is the focal stage in a Case-Based Reasoning (CBR) system. In this paper, a new case retrieval method called CRGCU is proposed in a systematical way, which is based on Genetic Algorithms (GAs) and Group Decision-Making method. First, feature attribute weights of cases are optimized by using GAs. Second, instead of utilizing only one set of feature attribute weights, we calculate similarity based on multiple sets of optimized weights. The result of case retrieval can be obtained at last by adopting Group Cardinal Utility function. The experiments on both static and dynamic data sets illustrate that our method is effective and suitable for CBR system.
  • Keywords
    case-based reasoning; decision making; genetic algorithms; CRGCU; case based reasoning system; case retrieval strategy; genetic algorithms; group cardinal utility function; group decision making method; Accuracy; Cognition; Databases; Decision making; Gallium; Iris; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5678347
  • Filename
    5678347