Study on tunnel settlement prediction method based on parallel grey neural network model

Lei Zhu; Teng Huang; Yue-qian Shen; Xian-min Zeng

doi:10.1117/12.2207838

9 December 2015 Study on tunnel settlement prediction method based on parallel grey neural network model

Lei Zhu, Teng Huang, Yue-qian Shen, Xian-min Zeng

Proceedings Volume 9808, International Conference on Intelligent Earth Observing and Applications 2015; 98082B (2015) https://doi.org/10.1117/12.2207838
Event: International Conference on Intelligent Earth Observing and Applications, 2015, Guilin, China

Abstract

In this paper, according to the characteristics of the grey forecast method and the neural network, constructed the parallel grey neural network model(PGNN) and apply to forecast a tunnel monitoring point’s settlement displacement data based on Nanjing metro. The results showed that the prediction accuracy of PGNN is significantly higher than that of unitary grey and neural forecast method. proves that the effectiveness of PGNN in the tunnel settlement prediction. Keywords: Tunnel settlement, grey model, neural network model, prediction

Citation Download Citation

Lei Zhu, Teng Huang, Yue-qian Shen, and Xian-min Zeng "Study on tunnel settlement prediction method based on parallel grey neural network model", Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98082B (9 December 2015); https://doi.org/10.1117/12.2207838

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