Deformation prediction of mining slope based on grey correlation analysis and GA-BP model

Yuejuan Chen; Qiuhuan Cai; Pingping Huang; Wei Xu; Xiaolong Liu

doi:10.1117/12.2667639

10 February 2023 Deformation prediction of mining slope based on grey correlation analysis and GA-BP model

Yuejuan Chen, Qiuhuan Cai, Pingping Huang, Wei Xu, Xiaolong Liu

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125521E (2023) https://doi.org/10.1117/12.2667639
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

In order to improve the prediction accuracy of the slope deformation prediction method in mining area, aiming at the problems of many disaster causing factors of slope deformation and BP neural network is easy to fall into local minimum value, a prediction method based on the combination of genetic algorithm and BP neural network based on grey correlation analysis is proposed. The grey correlation analysis method is used to screen the main influencing factors, and the factors with high correlation degree are used as input indexes to simplify the network structure. Then, the genetic algorithm is used to optimize the BP neural network to establish the GA-BP model, and finally the prediction is compared. The results show that the grey correlation analysis can further improve the consistency between the predicted value and the real value, and the model can accurately predict the slope deformation. The research results have important auxiliary reference significance for mine safety production.

Citation Download Citation

Yuejuan Chen, Qiuhuan Cai, Pingping Huang, Wei Xu, and Xiaolong Liu "Deformation prediction of mining slope based on grey correlation analysis and GA-BP model", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125521E (10 February 2023); https://doi.org/10.1117/12.2667639

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