一种改进的基于关联规则挖掘的遗传算法

A Kind of Improved Genetic Algorithm Based on Association Rules Mining

针对传统的遗传算法容易导致算法的过早收敛而陷于局部最优困境,或收敛时间过长而消耗大量的搜索时间的缺陷,该文提出了一种改进的遗传算法,该算法采用一种自适应变异率和改进的个体选择方法,并且将这种改进遗传算法应用于关联规则的挖掘,实验结果证明这种算法是有效的。

To the traditional genetic algorithm easily lead to premature convergence of the algorithm and into the plight of local optimum, or Convergence too much time and consume a large amount of time to search for flaws,this text proposed a kind of improved genetic algorithm, The algorithm adopts an adaptive mutation rate and improve the methods of individual choice, and this will improve the genetic algorithm used in the data mining association rules. The experimental results show that the efficiency of the algorithm for database.