基于改进AHP法的道路选线风险评估研究  

Research on the risk assessment of route alignment based on the improved AHP

作　　者：李军[1] 蒋世琼[1] 

机构地区：[1]中南大学土木工程学院,长沙410004

出　　处：《安全与环境学报》2013年第1期246-249,共4页Journal of Safety and Environment

基　　金：国家自然科学基金项目(50708117)

摘　　要：阐述了现行道路选线设计中存在的不确定因素对整体选线设计造成的影响,分析了在道路选线设计中引入风险评估思想,以风险估计结果作为选线设计可行性分析的一个重要参数的可行性和实用性。通过逆向风险识别思维,提出选线设计风险"隐因子"的概念,建立了风险识别HOI模型,即隐因子风险识别模型。基于该风险识别模型构建相应的风险指标层次结构体系,利用层次分析法与BP神经网络相结合的优化AHP法,结合各指标对选线风险的影响权值进行风险评价分析,对该类不确定因素进行综合评估。实例证明,风险评估的引入能够为选线设计可行性研究阶段线路方案的评价提供参考。This paper presents an improved risk assessment method in the design of road alignment. As is known, risk assessment can help the road designers to heighten the comprehensive view of their design- ing approach and ameliorate their subjective analysis of the environ- mental and economic uncertainties. It is from these actual needs that we would like to describe the impacts of uncertainties in route selec- tion and its relation to the entire work of road design. It is just for these purposes and other inclinations concerned, we should like to present our discussion on the feasibility and practicality of the risk as- sessment to be taken into account as an important reference to the feasibility analysis of the route alignment. Starting from this point, we have first of all put forward the ideas on fully considering on how to i- dentify ＂hidden factors＂ in the risk assessment process and the con- cept of reverse risk identification. The concept is by nature closely connected with the environmental and economic uncertainty in the stage of route selection. And, then, we have established the identifi- cation model, named＂HOI＂model, based on which we have built up the corresponding hierarchy of risk indicators. And, afterwards, we have adopted the method of combining the AI-IP and BP Neural Net- work for the actual risk assessment. In doing so, on the one hand, we have improved the method of optimizing the subjective effects by getting rid of too much human involvement when the AHP method is used independently. On the other hand, we have also increased the network uptime and operational precision due to the use of numerous sample data when BP neural network was used. Following these steps, we have done the comprehensive risk weights analysis of vari- ous indicators to assess the likely risk uncertainties. In the practical process, we tried to use eight representative sections of ShenHai Ex- pressway to verify our risk assessment model while taking into full consideration the influential factors in the assessment

关 键 词：道路工程 道路选线 风险评价 HOI模型 改进AHP法 

分 类 号：U412.32[交通运输工程—道路与铁道工程]