基于贝叶斯理论的区域可持续发展水平概率评估

针对目前区域可持续发展水平评估结果可信度不高的问题,研究了评估的不确定性对可持续发展水平概率的影响。通过统计分析,确定区域生态足迹值的影响要素,以此建立生态足迹值的贝叶斯回归方程,推求回归系数的先验分布和后验分布,再由马尔可夫链蒙特卡洛随机抽样及负生态足迹指数构建区域可持续发展水平的概率评估模型,并以武汉市为典型区,对该模型进行实例应用。结果表明,武汉市2000~2009年的可持续发展水平为Ⅳ级,概率为100%。计算结果与已有研究成果基本一致,表明该方法合理,可弥补确定性区域可持续发展水平评估模型的不足。

Probabilistic Assessment of Level of Regional Sustainable Development Based on Bayesian Theory

Aiming at the impact of uncertainty on assessment of regional sustainability level for the reason that the confidence of the assessment result is not accurate recently, this paper determines the influencing factors of the ecological footprint value by statistical analysis. And Bayesian regression formula of ecological footprint is established. At the same time, infer prior distribution and posterior distribution of regression coefficients are deduced. Then probabilistic assessment model of regional sustainability is established based on random sampling of Monte Carlo Markov chains and negative ecological footprint index (NEFI). Finally, The model was applied to Wuhan City. The results show that the sustainability level of Wuhan City in 2000 2009 belongs to grade IV, and the probability is 100%. The result is basically consistent with the existing research, which indicates that the method is rational. Therefore, Bayesian theory can make up the shortage of certain assessment model of regional sustainability.