基于层次聚类的科技创新人才成长模式研究

Growth Factor and Model Analysis for Creative Talents of Science and Technology based on Hierarchical Clustering

为了对科技创新人才的基本要素进行定量分析和仿真,探索科技创新人才培养和成长道路,收集各类科技创新人才和普通人员的七商共计32个素质指标的样本数据1222例,对样本集合进行自底向上的层次化聚类,进而进行类内的指标显著性分析,得出科技创新人才的关键素质集合。最终提出科技创新人才的七商可视化表示方法,指出低层人才向高层科技创新人才发展的成长路径。首次提出了科技创新人才基本素质的量化分析方案及基于要素的人才成长模式研究方法,仿真结果表明,基于层次聚类的科技创新人才量化方案具有一定的系统性、合理性和客观性。

To quantify and simulate the basic quality of creative talents, and to explore the path to growth of per- sonnel training, 1222 samples of seven quotients with thirty -two indices were collected in our research. By bottom - up hierarchical clustering and notability analysis, a critical factors and quality set of creative talents was obtained by calculation. Finally, a novel quotients visualization method was illustrated, and an effective path to growth of creative talents from low level to high level was proposed. It is the first solution for how to quantitatively investigate basic and critical factors and path to growth of creative talents of science and technology. The simulation results show that the proposed quantification scheme based on hierarchical clustering is of systematicness, validity and objectivity.