北京大学学报(自然科学版)

基于人工神经网络的城市拓展区可持续发展指数序列研究

郁亚娟,王真,郭怀成1 ,黄凯,王树通,刘永   

  1. 北京大学环境学院,北京,100871;1通讯联系人,E-mail: hcguo@pku.edu.cn
  • 收稿日期:2005-07-27 出版日期:2006-07-20 发布日期:2006-07-20

Application of Artificial Neural Ntwork in Urban Fringe's Sustainable Development Index Series

YU Yajuan, WANG Zhen, GUO Huaicheng1, HUANG Kai, WANG Shutong, LIU Yong   

  1. College of Environmental Sciences, Peking University, Beijing, 100871; 1Corresponding Author, E-mail: hcguo@pku.edu.cn
  • Received:2005-07-27 Online:2006-07-20 Published:2006-07-20

摘要: 基于压力-状态-效应(PSR)理论,着重分析我国传统农业地区在快速城市化过程中融入城市拓展区,并逐步城市化过程中的可持续发展问题,提出了一套以PSR为基础框架的城市拓展区可持续发展指标体系。基于灰色系统理论,将该特定区域的社会-经济-环境复杂巨系统作为灰箱系统模型,应用人工神经网络的人工智能方法,计算城市拓展区的可持续发展指数(ISD)。最后,将该方法应用于郑州惠济区的1987—2004年ISD时间序列评估,并作了不确定性分析。该方法可应用推广于类似的区域可持续发展的综合评价以及时间序列分析等问题。

关键词: PSR理论, 可持续发展指数, 人工神经网络, 惠济区

Abstract: Deriving from the Pressure-State-Response (PSR) theory, a framework of sustainable development (SD) indicators describing urban fringe's urbanization process was brought forward. Sustainable Development Index (ISD) series for multi-years were used to measure the regional capability of sustainability. The socio-economic-environmental grand system was considered as a grey system and artificial neural network (ANN) was applied to calculate the ISD series. Then a case study of Huiji District, Zhengzhou City was adopted for ISD assessment from the year 1987 to 2004, and uncertainty analysis was also construed. The results showed that both the framework and the ISD with ANN were suitable in reflecting its SD levels. The method is recommendable for analogous problems.

Key words: PSR theory, sustainable development index, artificial neural network, Huiji District

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