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首页> 外文期刊>Landslides >Establishment of a deformation forecasting model for a step-like landslide based on decision tree C5.0 and two-step cluster algorithms: a case study in the Three Gorges Reservoir area, China
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Establishment of a deformation forecasting model for a step-like landslide based on decision tree C5.0 and two-step cluster algorithms: a case study in the Three Gorges Reservoir area, China

机译：基于决策树C5.0的阶梯式滑坡变形预测模型的建立及两步簇算法：以三峡库区三峡库区为例

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摘要

This study presents a hybrid approach based on two-step cluster and decision tree C5.0 algorithms to establish a deformation forecasting model for a step-like landslide. The Zhujiadian landslide, a typical step-like landslide in the Three Gorges Reservoir area, was selected as a case study. Approximately, 6 years of historical records of landslide displacement, precipitation, and reservoir level were used to build the forecasting model. The forecasting model consisted of seven comprehensive rules governing hydrologic parameters and their magnitudes and was developed to predict landslide deformation. This model was applied to rapidly forecast the likelihood of step-like landslide deformation resulting from rainfall and water level fluctuations in the Three Gorges Reservoir area. Given the satisfactory accuracy of the trained model, the presented approach can be used to establish forecasting models for step-like landslides and to facilitate rapid decision making.
机译：本研究提出了一种基于两步集群和决策树C5.0算法的混合方法，以建立阶梯滑坡的变形预测模型。 选择了诸暨三峡水库区域的典型阶梯滑坡，作为案例研究。 大约是6年的旧滑坡排量，降水和水库水平的历史记录来构建预测模型。 预测模型包括七个综合规则，用于治疗水文参数及其大小，并开发出预测滑坡变形。 该模型应用于快速预测三峡库区中降雨量和水位波动引起的阶梯式滑坡变形的可能性。 鉴于培训模型的令人满意的准确性，所提出的方法可用于建立阶梯式山体滑坡的预测模型，并促进快速决策。

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