基于最大熵原理和属性区间识别理论的洪水灾害风险分析

针对复杂洪水灾害系统中随机、模糊、灰色等各种不确定性,结合洪水灾害风险管理广义熵智能分析的理论框架,以最大熵原理和属性区间识别理论为基础,建立了基于最大熵原理的洪水灾害风险属性区间识别模型(AIRM-POME),利用梯形模糊数和层次分析法相结合的方法确定评价指标权重,采用均化系数综合AIRM-POME计算得到的属性测度区间,由置信度准则和特征值公式对各评价单元进行危险、易损等级的评定和排序,并根据联合国对自然灾害风险的定义及其定量表达式给出风险等级。将模型应用到荆江分洪区洪水灾害风险分析中,实例研究表明,模型合理可靠,深层次地刻画了各种不确定性,是一种风险分析新方法,可推广应用到其他自然灾害的风险分析中。

Flood disaster risk analysis based on principle of maximum entropy and attribute interval recognition theory

There is currently stochastic,fuzzy and gray information in the complex flood disaster system.Furthermore,the theoretical analysis frame is based on general entropy and intelligence integration methodology for flood disaster risk management.The model(AIRM-POME) named attribute interval recognition model based on the principle of maximum entropy is proposed for flood disaster risk analysis.Then,the analytic hierarchy process is combined with trapezoidal fuzzy numbers to calculate the weights of criteria,and the average coefficient is applied to transform the attribute interval measure into an integrative attribute measure.In addition,the flood hazard grades and flood vulnerability grades can be obtained by using the assurance criterion and feature value equation.Finally,on the basis of the natural disasters risk expression recommended by the United Nations,risk grade for each unit can be achieved,respectively.AIRM-POME is employed for flood disaster risk analysis in Jingjiang flood diversion district,and the results demonstrate that the model is reasonable and has the advantage of illustrating very well the uncertainties.Thus,the model has bright prospects of application for comprehensive risk assessment of other natural disasters.