本文提出一种基于量子进化理论的小支持度关联规则挖掘算法。算法将模糊集的概念引入到原始数据离散化和支持度、置信度的定义当中，通过改进量子进化过程和适应度函数，实现在多个最优方向上的进化，可以获得满足不同目标的最优解集合。仿真实验表明，该算法能够从旅游突发事件中有效挖掘出各种小支持度的关联规则。%A low support association rules mining algorithm based on quantum evolution is proposed in this paper. The algorithm introduces fzzy sets into the discretization of original data and the definition of support and confidence. And we have improved the fitness function and evolution process to make population evolve in multi optimal directions. Thus the optimal solution set satisfied different objectives can be achieved. Simulation demonstrates the effectiveness of this method for mining low support association rules from tourism emergenciec
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