关键词: 聚类算法, 量子遗传算法, 模糊K-prototypes算法, 数值型属性, 数据挖掘

Abstract: Cluster analysis is most widely used in data mining as a technology；it has important applications in many fields.Fuzzy h-prototypes algorithm is one of the most effective algorithms of cluster analysis，however，the problem of sensitive to initial value and vulnerable to the problem of local minimum exists.In order to overcome the shortcomings，a hybrid algorithm based on quantum genetic algorithm and FKP clustering algorithm is proposed.The quantum genetic algorithm is used to determine the initial cluster center FKP firstly，and then the results of quantum genetic algorithm clustering result is used as start value of follow-up FKP.Experimental results show that the algorithm has good convergence and stability，better than single use of FKP algorithms and related improved algorithms.

Key words: clustering algorithm, quantum genetic algorithm, fuzzy K-prototypes algorithm, numerical attributes, data mining