Genetic-based search for error-correcting graph isomorphism

Author

Wang, Yuan-Kai ; Fan, Kuo-Chin ; Horng, Jorng-Tzong

Author_Institution

Inst. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chung-Li, Taiwan

Volume

27

Issue

4

fYear

1997

fDate

8/1/1997 12:00:00 AM

Firstpage

588

Lastpage

597

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

Keywords

convergence of numerical methods; error correction codes; genetic algorithms; optimisation; pattern recognition; query formulation; convergence speed; error-correcting graph isomorphism; genetic algorithms; genetic-based search; local search strategies; pattern recognition; premature convergence; searching criteria; selection operator; Buildings; Computer science; Convergence; Councils; Error correction; Genetic algorithms; Impedance matching; Optimization methods; Pattern recognition; Uncertainty;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/3477.604100

Filename

604100