基于EEMD-HW-PSO-ELM耦合模型的排土场边坡位移预测模型

doi:10.11872/j.issn.1005-2518.2022.04.164

Abstract

Abstract:

In order to accurately predict the displacement of waste dump slope with small samples and nonlinear characteristics，an EEMD-HW-PSO-ELM slope displacement combined prediction model based on empirical mode decomposition method，cubic exponential smoothing method and particle swarm optimization limit learning machine was proposed.Taking the GPS displacement monitoring data of Yiminhe open pit waste dump as an example to verify the effectiveness of the model，the research results show that the time series of slope displacement decomposed by EEMD model includes four IMF components and one margin.The decomposed data is reconstructed into trend term and fluctuation term with clear physical meaning.The cubic exponential smoothing method and particle swarm optimization limit learning machine were selected to predict the displacement of trend term and fluctuation term respectively.The equal weight superposition value is the final prediction result.The average relative error of the prediction value is 0.38% and the root mean square error is 1.15.BP model and Elman model were selected for comparative prediction.The results show that the com-bined prediction model has good prediction effect and can provide a theoretical basis for safety management.

Key words: dump, slope displacement, coupling model, integrated empirical mode decomposition, cubic exponential smoothing method, particle swarm optimization extreme learning machine

CLC Number:

TP18

Ensheng KANG,Zexi ZHAO,Haidong MENG. Displacement Prediction of Dump Slope Based on EEMD-HW-PSO-ELM Coupling Model[J].Gold Science and Technology, 2022, 30(4): 594-602.

Figures/Tables 11

Fig.1

Fig.2

Table 1

Dump slope monitoring data"

监测周期	变形值/mm	监测周期	变形值/mm
1	11.2	20	120.9
2	20.5	21	147.1
$?$	$?$	$?$	$?$
18	108.8	37	293.4
19	113.5	38	309.2

Table 1

Fig.3

Fig.4

Table 2

Displacement fluctuation term data"

监测周期	变形值/mm	监测周期	变形值/mm
1	-1.369963418	20	-14.34116986
2	2.559812446	21	4.116794032
$?$	$?$	$?$	$?$
18	-11.45177337	37	11.39798564
19	-14.3411961	38	17.43340374

Table 2

Table 3

Displacement trend item data"

监测周期	变形值/mm	监测周期	变形值/mm
1	12.81344111	20	135.2624154
2	18.16840321	21	142.9195574
$?$	$?$	$?$	$?$
18	120.3123143	37	281.9660058
19	127.7266764	38	291.6910052

Table 3

Fig.5

Fig.6

Table 4

Fig.7

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模型类型	MAE/%	RMSE
BP模型	3.96	12.16
Elman模型	7.67	24.99
EEMD-HW-PSO-ELM模型	0.38	1.15

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Displacement Prediction of Dump Slope Based on EEMD-HW-PSO-ELM Coupling Model

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