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Proceedings Paper

Study on tunnel settlement prediction method based on parallel grey neural network model
Author(s): Lei Zhu; Teng Huang; Yue-qian Shen; Xian-min Zeng
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Paper 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

Paper Details

Date Published: 9 December 2015
PDF: 7 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98082B (9 December 2015); doi: 10.1117/12.2207838
Show Author Affiliations
Lei Zhu, Hohai Univ. (China)
Teng Huang, Hohai Univ. (China)
Yue-qian Shen, Hohai Univ. (China)
Xian-min Zeng, Hohai Univ. (China)

Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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