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Research on Prediction and Optimization of Slope Deformation in Mining Area

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DOI: 10.23977/erej.2020.040110 | Downloads: 3 | Views: 235


Tianlong Wang 1, Hairui Zhang 2, Xiaorui Tao 3, Wei Chu 1


1 College of Civil Engineering & Architecture, China Three Gorges University, Yichang, 443002, China
2 College of Science, China Three Gorges University, Yichang, 443002, China
3 College of Economics & Management, China Three Gorges University, Yichang, 443002, China

Corresponding Author

Tianlong Wang


In this paper, a total of 25 periods of data from 3# monitoring points in the direction of the main slide of the slope were selected for model prediction accuracy validation. According to the volatility of the slope deformation detection data in the mining area, the slope deformation were predicted by three methods: conventional GM(1,1) model, the Autoregressive Integrated Moving Average model and BP neural network.


Deformation prediction, GM(1,1), ARIMA, BP neural network


Tianlong Wang, Hairui Zhang, Xiaorui Tao, Wei Chu, Research on Prediction and Optimization of Slope Deformation in Mining Area. Environment, Resource and Ecology Journal (2020) 4: 66-69. DOI:


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