Title :
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
fDate :
8/1/1997 12:00:00 AM
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;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.604100
