基于直觉模糊层次分析法的地震压埋率模型研究

Research on earthquake buried rate model based on intuitionistic fuzzy analytic hierarchy process

强烈地震会导致建筑物倒塌进而造成室内人员压埋,因此,把特定区域和建筑群的压埋率作为震后救援的决策指标尤为重要。但地震建筑物倒塌受多个影响因素共同作用,造成了压埋率模型的后验倒塌率评估的不确定性问题。针对这个问题采用直觉模糊层次分析法,选取了震级、震源深度、震中距、抗震设防烈度、地基和基础、建筑物结构类型和结构现状等七大影响因素进行加权分析。运用LINGO软件建模解算出了各影响因素权重,通过极大似然法估算了各影响因素对建筑物倒塌率的影响值,进而评估出了建筑物预估倒塌率,并结合先验在室率模型及其区划,建立了基于直觉模糊层次分析法的地震压埋率模型。最后以汶川灾区学校为例,进行了压埋率评估,并对其进行了误差分析。研究表明:抗震设防烈度、建筑物结构类型和结构现状是影响建筑物倒塌的主要因素;在实际评估中模型精度达到±0.15,能为震后快速应急救援提供决策辅助。

A strongearthquake can cause the collapse of buildings,which furthercauses buried indoor personnel.Therefore,it is particularly important to take the buried rate of specific areas and buildings as the decision-making indexforthe post-earthquake rescue.However,the collapse of buildings in earthquake is affected by many factors,which leads to the uncertainty of the post-validated collapse rate evaluation of the buried rate model.To address this problem,this paper adopts intuitionistic fuzzy analytic hierarchy process,and selects seven influential factors such as earthquake magnitude,depth of hypocenter,epicentral distance,seismic fortification intensity,buildingbase and foundation,building structure types and statusfor weighted analysis.The weight of each influencing factorsiscalculated by LINGO software,the impact value of each influencing factors on the building collapse rate is estimated by the maximum likelihood method,and then the buildings collapse rate is estimated.The model of the earthquake buried rate based on intuitionistic fuzzy analytic hierarchy process is established by combining the pre-validated in-buildings rate model and its regionalization.Taking the schools in the wenchuan disaster area as an example,the buried rate is evaluated and the error analysis is carried out.The research shows that the seismic fortification intensity,building structure types and statusare the main factors affecting building collapse;In the actual evaluation,the accuracy of the model is as high as“±0.15”,which can provide decision-making support for the rapidemergency rescue after the earthquake.