| 引用本文: | 吕蔚,王新峰,孙智信.基于核主成分分析的高校科技创新能力评价研究.[J].国防科技大学学报,2008,30(3):81-85.[点击复制] |
| LU Wei,WANG Xinfeng,SUN Zhixin.Application of the Kernel Principal Component Analysis Method to University S&T Innovation Capability Evaluation[J].Journal of National University of Defense Technology,2008,30(3):81-85[点击复制] |
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| 基于核主成分分析的高校科技创新能力评价研究 |
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(1.北京理工大学 管理与经济学院，北京100081;2.国防科技大学 信息系统与管理学院，湖南 长沙 410073)
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| 摘要: |
| 高校在国家创新体系中占有举足轻重的地位，高校科技创新能力评价研究对提高高校科技创新能力具有积极的意义。基于核主成分分析的评价方法能够有效去除高校科技创新能力评价指标体系中的非线性相关信息，从而取得较好的评价结果。以15所教育部直属高校科研统计数据为样本，利用核主成分分析法进行了高校科技创新能力评价的实证分析，并与主成分分析结果进行了比较，结果表明，核主成分分析能够取得更高的主特征值累积贡献率，从而产生更为合理的评价结果。 |
| 关键词: 科技创新能力评价 核主成分分析 评价指标 |
| DOI： |
| 投稿日期：2007-12-11 |
| 基金项目:“十一五”全国教育科学规划军队重点课题资助项目(PLA061003) |
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| Application of the Kernel Principal Component Analysis Method to University S&T Innovation Capability Evaluation |
| LU Wei1,2, WANG Xinfeng3, SUN Zhixin3 |
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(1.School of Management and Economics, Beijing Instituite of Technology, Beijing 100081, China;2. 2.College of Information System and Management, National Univ. of Defense Technology, Changsha 410073, China;3.2.College of Information System and Management, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| Universities play an important role in the national innovation system, and the research on the university S&T innovation capability evaluation is of great significance. Kernel principal component analysis(KPCA) method is proposed for the evaluation of university S&T innovation capability. This method, in comparison with Principal Component Analysis (PCA) method, can solve nonlinear correlation problem of evaluation index in the analysis of the S&T data released in 2002 from 15 universities directly subordinate to Chinese Ministry of Education. In particular, the result shows that contribution of the first and second principle components are more concentrated by KPCA than by PCA, and KPCA has better evaluation performance than PCA. |
| Keywords: S&T innovation capability evaluation kernel principal component analysis (KPCA) evaluation index |
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