Classification and Evaluation for the Midwest Regional Innovation Capability Based on Principal Component Analysis and Self-organizing Neural Network

摘要：

The imbalance of regional innovation capability is significantly prominent. Low regional innovation capacity of the Midwest limits the sustainable economic development in these regions. This paper selects main indexes data from high technology industrial technology activities in Midwest provinces in 2007 Chinas high technology industry statistics yearbook. Firstly, it reduces the correlations between variables by the principal component analysis. Secondly, it characterizes sample characteristic extracting 5 main components from 20 variables. Then it extracts 5 main components as input variables to build simulation model by using self-organizing neural networks. Midwest provinces are classified into seven groups. At last, it analyzes the classification reasons.

关键词： the midwest regional innovation capability principal component analysis self-organizing neural network

作者: Jian Yin Zhaofeng Diao Lingling Li

作者单位: School of Management, Wuhan University of Technology Wuhan, RP China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 22-25

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）