Genetic-based search for error-correcting graph isomorphism

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Abstract

Error-correcting graph isomorphism has been found useful in numerous pattern recognition applications. This paper presents a genetic-based search approach that adopts genetic algorithms as the searching criteria to solve the problem of error-correcting graph isomorphism. By applying genetic algorithms, some local search strategies are amalgamated to improve convergence speed. Besides, a selection operator is proposed to prevent premature convergence. The proposed approach has been implemented to verify its validity. Experimental results reveal the superiority of this new technique than several other well-known algorithms.

Original languageEnglish
Pages (from-to)588-597
Number of pages10
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume27
Issue number4
DOIs
StatePublished - 1997

Keywords

  • Error-correcting graph isomorphism
  • Genetic algorithms

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