CAJ | 학술논문

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。
채용심리량표방법대236명기업원공적조직분위화만의도진행료측량，침대K-means방법적결점，채용양자유전산법대원공적조직분위수거진행취류。운용10위양자비특위대취류중심적매일유수치진행편마，동시채용선전문방식대염색체진행질대연화。대취류소득3류원공적조직분위화만의도분수진행통계검험，결과표명，량자도존재현저성차이，설명운용양자유전산법진행취류시가행적，취류적결과대개진기업적관리수평구유이론삼고개치。
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 signiifcant 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.