基于BP神经网络的京津冀城市群可持续发展综合评价

在综合分析了京津冀城市群各城市功能定位的基础上,构建了包含经济发展、社会发展、科技创新和生态环境4个子系统的城市可持续发展评价指标体系,运用2006—2015年的数据,采用熵值法和BP神经网络对京津冀城市群可持续发展能力进行非线性测度与分类,结果较为理想。结果表明:(1)北京和天津处于高可持续发展水平,可持续发展能力在空间上呈现出以京、津为中心随距离递减的趋势,最南端的邯郸和邢台处于低可持续发展水平;(2)北京可持续发展能力呈现下滑趋势,其他城市可持续发展能力逐年稳步上升,大城市可持续发展压力较大;(3)城市在不同子系统中存在各自的优劣势。各个子系统在可持续发展中均起到重要作用,城市宜结合各自子系统的优、劣势制定具有针对性的发展对策。

Assessment of the sustainable development of the Beijing-Tianjin-Hebei urban agglomeration based on a back propagation neural network

Based on a comprehensive analysis of the functional orientation of each city in the Beijing-Tianjin-Hebei urban agglomeration, an urban sustainable development evaluation index system was constructed with four subsystems, including economic development, social development, scientific and technological innovation, and the ecological environment. The entropy method and a back propagation neural network were used to non-linearly measure and classify the sustainable development ability of Beijing-Tianjin-Hebei urban agglomeration during 2006-2015. The results show that: (1) Beijing and Tianjin are at a high level of sustainable development, and sustainable development decreases with increasing distance from Beijing and Tianjin. Handan and Xingtai are at a low level of sustainable development. (2) Beijing''s level of sustainable development exhibits a decreasing trend, while that of other cities is increasing. Large cities are associated with greater pressure on sustainable development. (3) Different cities have their own advantages and disadvantages in the different subsystems. Cities should develop targeted development strategies in combination with the advantages and disadvantages of their subsystems.