• DocumentCode
    2629780
  • Title

    A learning automata based artificial immune system for data classification

  • Author

    Azandaryani, A. H Momeni ; Meybodi, M.R.

  • Author_Institution
    Dept. of Comput. Eng., Amirkabir Univ. of Technol., Tehran, Iran
  • fYear
    2009
  • fDate
    20-21 Oct. 2009
  • Firstpage
    530
  • Lastpage
    535
  • Abstract
    In this paper we propose an artificial immune system in which learning automata are used to adaptively determine the values of its parameters. Learning automata are used for altering the shape of receptor portion of antibodies to better complementarily match the confronted antigen. In order to show the effectiveness of the proposed artificial immune computer experiments have been conducted. The result of experimentations confirms the effectiveness of the proposed model.
  • Keywords
    artificial immune systems; learning automata; pattern classification; artificial immune computer experiments; data classification; learning automata based artificial immune system; Artificial immune systems; Classification algorithms; Cloning; Fault detection; Humans; Immune system; Intrusion detection; Learning automata; Pathogens; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Conference, 2009. CSICC 2009. 14th International CSI
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4244-4261-4
  • Electronic_ISBN
    978-1-4244-4262-1
  • Type

    conf

  • DOI
    10.1109/CSICC.2009.5349634
  • Filename
    5349634
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2629780