摘要
本文在对2003年至2014年1823名国家杰出青年科学基金获资助者成长历程研究分析的基础上,采用稀疏矩阵对1823名杰出青年基金获资助者的成长历程,包括教育历程、工作历程与获奖历程所具有的11个属性,进行三维空间的表示与存储。以平均教育历程作为杰青基金获资助者的基准趋势历程,在此基础上,针对每位杰青基金获资助者的成长历程相较于基准趋势历程之间的差异,分别定义各历程所包含的各个属性的偏离度,采用粒子群算法(PSO)寻找每个属性的权重值的最优解,分析每个权重值具体的实际意义,以及成长历程中各属性对杰青基金获资助者成长成才的影响,探索我国青年科技创新人才的培养方向。
Based on analysis of the growing course of the 1823 National Science Fund for Distinguished Young Scholars grantees from 2003 to 2014, we use sparse matrix to make three-dimensional space representation and storage of 11 properties of growing course,including the course of education, working and winning. On the basis of setting average education course as standard trend course of Distinguished Young Scholars grantees, and aiming at the differences between the two courses, we definite 4ach attribute＇s deviation included in each course, use PSO algorithm to find the optimal solution of each attribute＇s weight value of, analyze the practical significance of each weight value, and analyze the impact of each attributes on Distinguished Young Scholars grantees, so as to explore the training orientation of national innovation talents of science and technology.
出处
《高等工程教育研究》
CSSCI
北大核心
2016年第6期81-86,117,共7页
Research in Higher Education of Engineering
基金
国家社会科学基金(教育学)重点项目:"社会变迁过程中青少年价值观的发展与影响机制研究"(AEA160005)
