• DocumentCode
    3363727
  • Title

    Attribute reduction algorithm of rough set fused with ant colony algorithm

  • Author

    Xue Qing ; Hu Tao ; Cao Bowei

  • Author_Institution
    Simulation Center, Acad. of Armored Force Eng., Beijing, China
  • Volume
    5
  • fYear
    2011
  • fDate
    12-14 Aug. 2011
  • Firstpage
    2385
  • Lastpage
    2387
  • Abstract
    This paper fused rough set theory and ant colony algorithm. The attribute core was determined through the correlative algorithms of rough set, which could be used as initial node of ant colony algorithm, then the time complexity and search space were reduced. The search capacity was used to get the lease combination of these nodes, which is the minimal attribute set, and the NP-hard problem in attribute reduction by using rough set was avoided. The result of experiment showed the feasibility and validity of this algorithm.
  • Keywords
    computational complexity; optimisation; rough set theory; NP-hard problem; ant colony algorithm; attribute reduction algorithm; rough set theory; time complexity reduction; Algorithm design and analysis; Cities and towns; Complexity theory; Heuristic algorithms; Machine learning algorithms; Search problems; Set theory; ant colony algorithm; attribute reduction; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
  • Conference_Location
    Harbin, Heilongjiang, China
  • Print_ISBN
    978-1-61284-087-1
  • Type

    conf

  • DOI
    10.1109/EMEIT.2011.6023590
  • Filename
    6023590
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3363727