GENETIC-BASED SEARCH FOR ERROR-CORRECTING GRAPH ISOMORPHISM

Error-correcting graph isomorphism has been found useful in numerous p attern recognition applications, This paper presents a genetic-based s earch approach that adopts genetic algorithms as the searching criteri a to solve the problem of error-correcting graph isomorphism, By apply ing genetic algorithms, some local search strategies are amalgamated t o improve convergence speed, Besides. a selection operator is proposed to prevent premature convergence, The proposed approach has been impl emented to verify its validity, Experimental results reveal the superi ority of this new technique than several other well-known algorithms.