基于CEEMDAN理论的堆积层滑坡位移区间预测模型及仿真

Displacement interval prediction model and simulation of accumulation landslide based on ceemdan theory

为更好地控制滑坡灾害风险,最大程度降低灾害损失,提出了基于CEEMDAN理论的堆积层滑坡位移区间预测模型及仿真。利用多类型传感器采集滑坡信息,采用自适应完备集合经验模态分解算法计算样本熵,根据相关系数获取噪声所在区间,通过设定的合理阈值去除信号噪声;构建多传感器数据融合分布式架构,提高滑坡数据的全面性;通过构建预测模型,经过样本训练,输出最终预测结果。仿真实验表明:本文模型预测区间覆盖率较高,且区间宽度低,保证了预测精度。

In order to better control the landslide hazard risk and reduce the disaster loss to the greatest extent, a prediction model and simulation of landslide displacement interval of accumulation layer based on CEEMDAN theory were proposed. The landslide information is collected by multi type sensors, the sample entropy is calculated by the adaptive complete set empirical mode decomposition algorithm, the noise range is obtained according to the correlation coefficient, and the signal noise is removed by the set reasonable threshold;Construct a distributed architecture of multi-sensor data fusion to improve the comprehensiveness of landslide data;The final prediction results are output through the construction of prediction model and sample training. The simulation results show that the proposed model has high prediction interval coverage and low interval width, ensure the prediction accuracy.