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A Novel Immune Clonal Algorithm

  • Yangyang Li
  • Fang Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)

Abstract

This paper proposes a novel immune clonal algorithm, called a quantum-inspired immune clonal algorithm (QICA), which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QICA is also characterized by the representation of the antibody (individual), the evaluation function, and the population dynamics. However, in QICA, antibody is proliferated and divided into a set of subpopulation groups. Antibodies in a subpopulation group are represented by multi-state gene quantum bits. In the antibody’s updating, the scabilitable quantum rotation gate strategy and dynamic adjusting angle mechanism are applied to guide searching. Theoretical analysis has proved that QICA converges to the global optimum. Some simulations are given to illustrate its efficiency and better performance than its counterpart.

Keywords

Clonal Selection Artificial Immune System Clonal Size Antibody Population Clonal Selection Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yangyang Li
    • 1
  • Fang Liu
    • 2
  1. 1.Institute of Intelligent Information ProcessingXidian UniversityXi’anChina
  2. 2.Computer schoolXidian UniversityXi’anChina

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