The accurate and rapid prediction of landslide dam stability is of great significance for emergency response planning. However, current rapid prediction methods for the landslide dam cannot quantitatively consider the influence of landslide debris grain size distribution. A database was established based on 1434 documented historical landslide dams, including formed-unstable and formed-stable cases from around the world. The logistic regression method was utilized to develop new methods for the rapid prediction of landslide dam stability, which can consider the morphological characteristics and particle composition of the landslide dams as well as the hydrodynamic conditions of the upstream dammed lake. According to the available information on landslide debris particle composition, the newly proposed rapid prediction methods were classified as either detailed or simplified based on 27 and 150 cases, respectively. Based on the database, several typical methods for the rapid prediction of landslide dam stability were chosen to compare with the newly proposed methods. The performances of each method testify to the rationality of the new methods.

中文翻译：

---

基于Logistic回归的滑坡坝稳定性快速预测

准确、快速地预测滑坡坝体稳定性对应急预案具有重要意义。然而，目前的滑坡大坝快速预测方法无法定量考虑滑坡碎屑粒度分布的影响。一个数据库是基于 1434 个记录在案的历史滑坡坝建立的，包括来自世界各地的形成不稳定和形成稳定的案例。利用Logistic回归方法开发了一种新的滑坡坝稳定性快速预测方法，该方法可以考虑滑坡坝的形态特征和颗粒组成以及上游堰塞湖的水动力条件。根据现有的滑坡碎屑颗粒成分信息，新提出的快速预测方法分别基于 27 和 150 个案例分为详细或简化。基于该数据库，选取几种典型的滑坡坝体稳定性快速预测方法与新提出的方法进行比较。每种方法的性能都证明了新方法的合理性。