摘要： 介绍了量子势能、量子力学中粒子的分布机制和量子聚类算法，给出了量子聚类QC算法的物理理论根据，指出了量子聚类算法的优点和不足，提出了一种基于度量距离改变的量子聚类算法DQC，该算法对IRIS样本的聚类准确率比QC算法高出了8个百分点，实验结果证明了该算法的有效性。

关键词: 量子聚类算法, 量子势能, 聚类度量, 量子聚类分析

Abstract: This paper introduces quantum potential, distribution mechanism of particle, a quantum clustering algorithm, gives the physical essence of the quantum clustering algorithm, and points out its advantage and the shortcoming. Based on the above, an improved algorithm distance-based quantum clustering(DQC) is produced. The cluster accuracy ratio of DQC about the IRIS dataset outperforms that of QC 8%. Experimental results demonstrate its higher efficiency and better performance.

Key words: quantum clustering algorithm, quantum potential, clustering measure, quantum clustering analysis

中图分类号: 

• TP18