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量子遗传算法对组织氛围的聚类分析

Clustering Organizational Atmosphere Perception with Quantum Genetic Algorithm

  • 摘要: 采用心理量表方法对 236 名企业员工的组织氛围和满意度进行了测量, 针对 K-means 方法的缺点, 采用量子遗传算法对员工的组织氛围数据进行聚类。运用 10 位量子比特位对聚类中心的每一维数值进行编码, 同时采用旋转门方式对染色体进行迭代演化。对聚类所得 3 类员工的组织氛围和满意度分数进行统计检验, 结果表明, 两者都存在显著性差异, 说明运用量子遗传算法进行聚类是可行的, 聚类的结果对改进企业的管理水平具有理论参考价值。

     

    Abstract: The organizational atmosphere perception and satisfaction of 236 staff were measured with psychological scale. To overcome shortcomings of K-means, quantum genetic algorithm was used to cluster the data of organizational atmosphere. Each dimensional data of cluster center was coded with 10 quantum bits. The chromosomes were iteratively evaluated with rotation gate. Three categories of staff were obtained. There were significant differences of organizational atmosphere and satisfaction scores among the categories. It means that the cluster analysis with quantum genetic algorithm is feasible. The result is valuable to improve the management level for the enterprise.

     

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