基于CEEMDAN理论的堆积层滑坡位移区间预测模型及仿真

doi:10.13229/j.cnki.jdxbgxb20220076

Abstract

Abstract:

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.

Key words: adaptive empirical mode decomposition, sample entropy, particle swarm optimization, support vector machine, accumulation landslide displacement

CLC Number:

TP318.2

Jian WU,Bin XU. Displacement interval prediction model and simulation of accumulation landslide based on ceemdan theory[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(2): 562-568.

Figures/Tables 7

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参数类型	数值
含水量/%	12
密度/（g·cm3）	2.03
黏聚力/kPa	25.7
内摩擦角度/（°）	24.6

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

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