Chen Yu, Shu Longcang, Burbey Thomas J
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China.
Risk Anal. 2014 Apr;34(4):656-69. doi: 10.1111/risa.12182. Epub 2014 Mar 4.
Land subsidence risk assessment (LSRA) is a multi-attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor-level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster-Shafer (D-S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi-Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information--quantitative or qualitative, complete or incomplete, and precise or imprecise--to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.
地面沉降风险评估（LSRA）是一个多属性决策分析（MADA）问题，其特征通常是具有各种不确定性的定量和定性属性。因此，需要使用能够处理不确定性的方法对该问题进行建模和分析。在本文中，我们提出了一种基于证据推理（ER）算法和模糊集理论的综合评估模型。该评估模型构建为一个层次框架，将地面沉降风险视为两个关键因素的综合：危险性和脆弱性。这些因素可以通过一组由评估等级定义的基本指标来描述，这些指标具有将数值数据和主观判断转换为置信结构的属性。危险性和脆弱性的因素级属性使用ER算法进行组合，该算法基于由Dempster-Shafer（D-S）理论计算的置信结构信息以及由模糊集理论计算的分布式模糊置信结构。组合算法的结果产生分布式评估等级矩阵。该模型在中国西溪-城南地区的应用说明了其在地面沉降风险评估中的实用性和有效性。该模型利用所有类型证据的组合，包括所有评估信息——定量或定性、完整或不完整、精确或不精确——以提供基于危险性和脆弱性定义风险评估的评估等级。结果将使风险管理者能够根据计算出的风险状态应用不同的风险预防措施和缓解规划。
