• DocumentCode
    2387771
  • Title

    MHC Regulation Based Immune Formula Discovering Algorithm (IFDA)

  • Author

    Hu, Min ; Sun, Weiming

  • Author_Institution
    Shanghai Univ., Shanghai
  • fYear
    2007
  • fDate
    2-4 Nov. 2007
  • Firstpage
    605
  • Lastpage
    605
  • Abstract
    After having analyzed the advantage and disadvantage of gene expression programming (GEP), this paper proposes an innovative immune formula discovering algorithm (IFDA), which is actually inspired by MHC (major histocompatibility complex) regulation principle of immune theory. In IFDA, the formula are mapped as tree structure and transformed into both constant and variation section of antibody with a depth- first mechanism while its fragment is encoded into the MHC. Using the feature of MHC regulation, IFDA provides a quick solution to discover the proper formula. Many benchmark data are used for verifying the performance of IFDA in which all results from experiments show that the IFDA can really provide better performance than GEP.
  • Keywords
    artificial immune systems; genetic algorithms; tree data structures; tree searching; MHC regulation; depth-first mechanism; gene expression programming; immune formula discovering algorithm; immune theory; major histocompatibility complex regulation principle; tree structure; Algorithm design and analysis; Amino acids; Electronic mail; Gene expression; Genetic programming; Immune system; Partial response channels; Protection; Sun; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing, 2007. GRC 2007. IEEE International Conference on
  • Conference_Location
    Fremont, CA
  • Print_ISBN
    978-0-7695-3032-1
  • Type

    conf

  • DOI
    10.1109/GrC.2007.28
  • Filename
    4403171