One of the most important natural hazards is landslides that after the earthquake and floods cause the highest damage to humans. Nowadays, landslide events are taken into consideration by the experts in this domain and their mapping and detecting always is one of the important concerns. One of the useful methods is multi-criteria decision making that is used in order to prioritize landslide-prone zones. These methods perform based on several quantitative or qualitative criteria. Multi-criteria decision-making methods that have been the focus of researchers in recent decades use several measurement criteria instead of one. However, due to the broadness and diversity of existing methods the selection of a proper approach has become cumbersome; therefore, selecting a reliable technique for landslide evaluation can be of a great interest. In this study MCDM methods (VIKOR, PROMETHEE II, and permutation) were applied in order to detect and map landslide-prone points. Then obtained results were assessed by using prediction area (P–A) technique. Consequently, the intersection points of the P–A plot for PROMETHEE II model show 82 percent of landslide occurrences predicted only in 18 percent of the study area, while the intersection point of the P–A plot for permutation and VIKOR models shows 67 and 73 percent of landslide occurrences predicted only in 33 and 27 percent of the study area, respectively.

最重要的自然灾害之一是山体滑坡，在地震和洪水之后对人类造成的损失最大。如今，滑坡事件已被该领域的专家考虑在内，其绘图和检测一直是重要的关注点之一。一种有用的方法是多标准决策，用于确定滑坡易发区的优先级。这些方法基于几个定量或定性标准执行。近几十年来一直是研究人员关注的多标准决策方法使用多个测量标准而不是一个。然而，由于现有方法的广泛性和多样性，选择合适的方法变得很麻烦；因此，选择一种可靠的滑坡评估技术非常重要。在这项研究中，MCDM 方法（VIKOR、PROMETHEE II 和置换）被用于检测和绘制滑坡易发点。然后通过使用预测区域（P-A）技术评估获得的结果。因此，PROMETHEE II 模型的 P-A 图的交点显示仅在 18% 的研究区域内预测了 82% 的滑坡发生，而置换的 P-A 图和 VIKOR 模型的交点显示了 67 和 73仅在 33% 和 27% 的研究区域内预测了滑坡发生的百分比。