摘要
提出了用基于加速遗传算法的模糊层次分析法确定影响因子权重,用频率分析方法构造分类集合,然后采用集对分析方法从同、异、反三方面对预测当前年的区域生态足迹的影响因子集与分类集合的影响因子的距离进行定量计算,将分类集合生态足迹中心值的加权平均值作为当前年生态足迹的预测值,进而建立了用集对分析聚类预测方法进行区域生态足迹动态预测的(SPA-CP)具体实施方案。应用结果说明,这套建模方案的物理概念清晰,计算简便,精度较高,通用性较强,在不同区域生态足迹动态预测中具有一定的应用价值。
The accelerating genetic algorithm based fuzzy analytic hierarchy process is used to determine the weights of the influencing factors. The classified subsets of the history samples of regional ecological footprint and its influencing factors are constructed using the frequency analysis method. Set pair analysis method is used to quantitatively compute the distance between the nonce and the classified subsets vectors from the view of identical, discrepant and contrary degree; the weighted average of the center values of the classified subsets can be regarded as the predicted value of the nonce regional ecological footprint; and then a scheme of set pair analysis classified prediction method（SPA-CP） is established. The results show that the physical concept of SPA-CP is clear; its computation method is convenient; and its precision is high.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2008年第9期973-977,共5页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(50579009)
国家教育部人文社会科学规划基金资助项目(05JA840011)
关键词
区域可持续发展评价
生态足迹
动态预测
集对分析
模糊层次分析法
evaluation of regional sustainable developments ecological footprints prediction of dynamic change
set pair analysis
fuzzy analytic hierarchy process
