The Chongqing section of the Three Gorges Reservoir area (TGRA) is a high-risk geological catastrophe warning zone in the Yangtze River Basin. This study aimed to categorize landslides and improve the accuracy of landslide susceptibility evaluations by combining the artificial neural networks (ANN) and the normalized frequency ratio (NFR) models. Considering that the indicator factors have different effects on various landslides, the landslides were separated into four types, that is, giant, large, medium, and small. Thirteen indicator factors were selected through correlation analysis, including elevation, lithology, precipitation, land use, population density, and so on. Combined with 7777 historical landslide events, an ANN-NFR coupling model was proposed. The susceptibility grade prediction of landslides for the entire region was conducted using a GIS platform. Compared to the NFR model, the ANN-NFR model could improve the accuracy of landslide susceptibility evaluation by approximately 4%. This indicates that the ANN-NFR model is an effective method to calculate the weights of indicator factors. The FR value of large landslides is 9.201 in the very susceptibility region, and the model evaluation effect is superior to that of the other three types of landslides. The success rate of the ANN-NFR model after landslide classification was 78.9%, and the prediction rate was 78.6%, both of which were greater than the unclassified ANN-NFR model. Therefore, the ANN-NFR (landslide classified) model could improve the prediction accuracy and can provide a scientific basis for disaster prevention, mitigation, and management in the TGRA.

中文翻译：

---

基于滑坡分类和ANN-NFR模型的三峡库区滑坡敏感性评价

三峡库区重庆段是长江流域地质灾害高风险警戒区。本研究旨在通过结合人工神经网络（ANN）和归一化频率比（NFR）模型对滑坡进行分类，提高滑坡敏感性评估的准确性。考虑到指标因子对各类滑坡的影响不同，将滑坡分为巨型、大型、中型、小型四种类型。通过相关分析，选取海拔、岩性、降水量、土地利用、人口密度等13个指标因子。结合7777起历史滑坡事件，提出了ANN-NFR耦合模型。利用GIS平台对整个地区的滑坡敏感性等级进行了预测。与NFR模型相比，ANN-NFR模型可以将滑坡敏感性评价的精度提高约4%。这表明ANN-NFR模型是计算指标因素权重的有效方法。大型滑坡在极易感区的FR值为9.201，模型评价效果优于其他三类滑坡。滑坡分类后的ANN-NFR模型成功率为78.9%，预测率为78.6%，均大于未分类的ANN-NFR模型。因此，ANN-NFR（滑坡分类）模型可以提高预测精度，为TGRA防灾减灾和管理提供科学依据。