基于BP神经网络的河南省可持续发展能力评价
2016-10-19孟天醒文倩范慧平
孟天醒 文倩 范慧平


摘要:以河南省为例,构建了包含28项指标的可持续发展评价指标体系,涵盖经济、资源环境和社会三个子系统。基于2003-2012年河南省相关数据,运用人工神经网络理论和方法对河南省的可持续发展能力进行评价分析。结果表明,河南省可持续发展能力呈逐步提升态势,偶有波动;河南省各子系统可持续发展水平也为整体上升趋势,其中资源环境子系统20年间变化区间固定在4~8之间;经济子系统水平2003年之前变化较小,2004年开始明显提升;社会子系统呈现稳步上升态势,状态最为稳定。
关键词:可持续发展;BP神经网络;河南省
中图分类号:X22 文献标识码:A 文章编号:0439-8114(2016)05-1333-03
DOI:10.14088/j.cnki.issn0439-8114.2016.05.061
Analysis on Sustainable Development Ability in Henan Province Based on
BP Neural Network
MENG Tian-xing,WEN Qian,FAN Hui-ping
(College of Resources and Environment, Henan Agricultural University, Zhengzhou 450002, China)
Abstract: Taking Henan province as an example, the sustainable development evaluation index system was built which consisted of 28 indicators and 3 subsystems of economic, resource environment and the society. Based on relevant data from 2003 to 2012 of Henan Province, using the theory and method of artificial neural network in Henan province sustainable development ability evaluation and analysis, the results showed that the ability of sustainable development in Henan province was gradually improved, but occasionally fluctuated; the same as the sustainable development level of three subsystems in Henan province, in which changes in resources and environment subsystem was always between 4~8. And the economy subsystem level changed little before 2003 and it elevated obviously since 2004. Moreover, social subsystem was gradually rising and the level was the most stable.
Key words: sustainable development; BP neural network; Henan province
区域可持续发展是一个由资源环境、经济和社会三大子系统共同构成的复合生态系统,是三方面的协调发展[1]。由于各地区社会经济条件及其自然环境差异,可持续发展评价指标体系没有一个统一的标准,方法也各异[2]。国内外对可持续发展能力评价的研究多采用层次分析法[3]、生态足迹法[4]及DEA和因子分析法[5]。目前针对河南省进行的区域可持续发展能力评价研究较少,乔家君[6]运用改进熵值法进行定量分析,认为经济因子最为重要;指出要大力发展生产力,保证生态环境不退化,另外要控制人口增长。王安周等[7]运用生态足迹理论,结合人文发展指数、R/S分析方法,多角度探讨了河南省可持续发展状况。结果表明,河南经济发展在很大程度上是以环境、资源牺牲为代价的;……
