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Application of a two-step cluster analysis and the Apriori algorithm to classify the deformation states of two typical colluvial landslides in the Three Gorges, China

机译:应用两步聚类分析和Apriori算法对中国三峡两类典型的山崩滑坡的变形状态进行分类

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Several extensive landslides have occurred in the vicinity of the Three Gorges Reservoir since its initial impoundment in June 2003. A reduction of the landslide risk is essential for the safety and security of lives and property in the region. This study analyses the deformation states of two typical colluvial landslides (the Baijiabao and Laoshewo landslides) using 6 years of monitoring data, a two-step cluster analysis, and the Apriori algorithm. The landslide displacement versus time curves exhibit step-like patterns, and the landslide deformation is highly correlated with fluctuations in the reservoir level and seasonal precipitation. To determine different types of landslide deformation, the monthly displacement curves of the colluvial landslides are classified into three types using a two-step cluster analysis: initial deformation, constant deformation, and rapid deformation. Five driving factors were selected as the antecedents for the Apriori algorithm to obtain rules that describe the relationships between the landslide deformation and the influential parameters. These factors include the cumulative precipitation over the previous month, the maximum daily precipitation during the current month, changes in the reservoir level over the previous month, cumulative increases in the reservoir level and the average reservoir level during the current month. The analytical results were validated by comparing them with observed landslide deformation characteristics using three measurement standards: support, confidence and lift. The results show that the combined method of a two-step cluster analysis with the Apriori algorithm can effectively model the landslide deformation states that are associated with the Baijiabao and Laoshewo landslides. Moreover, this method may serve as a potential reference for deformation analyses of colluvial landslides in the Three Gorges.
机译:自三峡水库于2003年6月开始蓄水以来,在其附近发生了数次大规模滑坡。降低滑坡风险对于该地区生命和财产的安全与保障至关重要。本研究使用6年的监测数据,两步聚类分析和Apriori算法,分析了两种典型的河道滑坡(白家堡和老舍窝滑坡)的变形状态。滑坡位移与时间的关系曲线呈阶梯状,滑坡变形与储层水位和季节降水的波动高度相关。为了确定不同类型的滑坡变形,通过两步聚类分析将山崩滑坡的月位移曲线分为三种类型:初始变形,恒定变形和快速变形。选择了五个驱动因素作为Apriori算法的先决条件,以获得描述滑坡变形与影响参数之间关系的规则。这些因素包括前一个月的累计降水量,当月的最大每日降水量,前一个月的水库水位变化,当月的水库水位累积增加和平均水库水位。通过使用三种测量标准将其与观察到的滑坡变形特征进行比较,从而验证了分析结果的有效性:支撑,置信度和升力。结果表明,采用两步聚类分析与Apriori算法相结合的方法可以有效地模拟与白家堡和老舍窝滑坡有关的滑坡变形状态。而且,该方法可作为三峡冲积山体滑坡变形分析的潜在参考。

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