基于BP神经网络与熵值法的浙江省城市韧性评估研究

以浙江省为例, 利用BP神经网络与熵值法综合建模, 对2011—2020年间浙江省各地级市的城市韧性进行定量评价, 分析经济、社会、环境、设施4项城市单系统韧性及其复合韧性, 从而揭示浙江省城市韧性的空间分布特征与发展规律. 研究表明: 浙江省韧性发展趋势较为平稳, 韧性水平的空间分布差异较大, 内部存在发展不均衡现象; 核心地区与边缘地区的韧性水平均呈现缓慢上升势态, 且分异格局短期内不会发生改变.

Evaluation of urban resilience in Zhejiang Province based on BP neural network model and entropy method

Taking Zhejiang province as an example, this paper conducts a quantitative evaluation of the urban resilience for prefecture-level cities in Zhejiang province from 2011 to 2020 by applying BP neural network and entropy method. Analyzes are made in terms of the single system resilience of economy, society, environment and facilities and their composite resilience, the purpose of which is to reveal the spatial distribution characteristics and development rules of urban resilience in Zhejiang province. The results suggest that the development trend of toughness in Zhejiang province is relatively stable, the spatial distribution of toughness level is variant from place to place, and the internal development is unbalanced. The toughness levels of both core and marginal regions show a trend of slow growth, and the differentiation pattern will not change in the short term.