基于RBF神经网络视角的区域次级中心城市选择发展研究——以云南为例

Research on the Selection and Development of Regional Secondary Center City Based on RBF Neural Network—Taking Yunnan Province as an Example

省域次级中心城市选择问题,是区域平衡发展、协调发展的关键,目前选择区域次级中心城市的方法多为定性探讨,存在科学性和满意性较差等缺陷。从系统角度出发辅助决策,基于径向基神经网络构建能够综合考虑多种指标因素的选择模型,并以云南省为例进行实证论证,最后围绕发展次级中心区域经济、协同重构区域功能布局、加强区域间人才、技术联系等提出了发展建议。

Selecting the best sub - center city is the key problem of balanced and coordinated development of a province. However, traditional approaches are mostly qualitative, resulting in poor scientificness and satisfaction of decision making. To overcome the above drawbacks, a selecting model is presented in this paper, whichtakes into consideration multiple indexes based on the radial basis function neural network. After that, Yunnan province is cited for the empirical demonstration. Finally, we put forward some suggestions on how to develop regional secondary center city, including developing sub - regional economic center, collaborating and reconstructing the functional layout of the region, and strengthening the contact between areas in talents and technology.