基于指数移动平均线的渐变型滑坡变形加速开始点识别研究

    IDENTIFICATION OF CREEP LANDSLIDES ONSET OF ACCELERATION BASED ON EXPONENTIAL MOVING AVERAGE

    • 摘要: 滑坡预警预报是滑坡研究的热点和难点。速度倒数模型的简捷性和有效性使之成为广泛使用的临滑预报模型。滑坡变形加速开始点(Onset of Acceleration)直接影响到速度倒数模型的预报精度。本文基于经济学领域广泛使用的指数移动平均线,提出了准确识别滑坡变形加速开始点的方法:(1)将滑坡速度绝对值化;(2)定义趋势变化指数ω,利用滑动时间窗口法,识别滑坡加速趋势区;(3)对加速趋势区进行速度倒数线性拟合,根据线性拟合的相关性系数,识别滑坡加速变形开始点。在此基础上,以云南省区布嘎渐变型滑坡为例,对模型识别出的OOA点准确性进行了验证,结果表明:利用本文提出的方法,可准确识别渐变型滑坡的OOA点,利用识别的OOA点对后续数据进行线性回归,其相关性系数在0.8以上,预测误差在4d以下,显示出较好的预测结果。

       

      Abstract: Predicting the failure time of landslides remains a significant challenge in landslide research. The inverse velocity method is widely employed for landslide failure time prediction due to its effectiveness and practicality. The accurate identification of the onset of acceleration(OOA)critically influences the predictive results of this method. To address this,we present a straightforward approach for identifying OOA based on the exponential moving average technique,commonly used in economics. The method involves three steps: (1)analyzing absolute velocity values; (2)defining a trend change index ω and identifying acceleration trend zones using a moving time window technique; and(3)performing linear regression analysis on inverse velocity within acceleration zones,with OOA points determined based on correlation coefficients. Applied to the Qubuga landslide case,the model demonstrated effective identification of OOA points,with correlation coefficients exceeding 0.8 and prediction errors of less than four days,confirming the method's practical utility.

       

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