Study on Adaptive Genetic Simulated Annealing Algorithm in Association Rules Mining

Abstract

Premature occurring in the process of web log association rule mining by genetic algorithm may lead to no globally optimal solution. In order to avoid such a situation, this paper proposes Web log mining algorithm of association rules based on adaptive genetic strategy, simulated annealing. Based on genetic simulated annealing strategy, the algorithm ensures the diversity of the population from one generation to the application of parallel processing technology. In addition, this algorithm introduces the adaptive crossover probability and mutation probability so as to improve the algorithm's global searching ability. Experimental results show that this algorithm can significantly enhance mining speed and can effectively avoid premature, thus of better strong global convergence.