摘要
文章利用径向基神经网络模型对我国十大城市群自主创新能力进行测度分析,构建城市群自主创新能力测度指标体系,建立自主创新能力及其创新要素与评价指标间的径向基神经网络模型,计算得到十大城市群2011—2015年自主创新能力及其创新要素的测度得分,评估城市群内部自主创新能力的协调发展程度,分析城市群自主创新能力发展现状,文章最后提出四大类城市群各自的提高自主创新能力及其协调发展程度的建议。
The self-innovation capability of top ten urban agglomerations in China is measured based on radial basis function （RBF） neural network. The index system for measuring self-innovation capability of urban agglomerations was established, RBF neural network model between self-innovation capability and evaluation indexes was developed, measurement scores for the self-innovation capability and its innovation elements of the top ten urban agglomerations between 2011-2015 were obtained, and coordinated development degree for self-innovation capability of each urban agglomeration was evaluated. Based on evaluation results, development status of self- innovation capability of the top ten urban agglomerations was analyzed, and policy suggestions for improvement of self- innovation capability and its coordinated development degree were proposed.
出处
《改革与战略》
2018年第2期136-141,共6页
Reformation & Strategy
基金
湖南省高等学校科学研究项目-重点项目(项目编号:17A234)
湖南省情与决策咨询研究项目资助(项目标号:2015BZZ081)阶段性成果
关键词
城市群
自主创新能力
协调发展
径向基神经网络
urban agglomerations
self-innovation capability
coordinated development
RBF neural network
