Proceedings Paper
Study on tunnel settlement prediction method based on parallel grey neural network model| Format | Member Price | Non-Member Price |
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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
Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)
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
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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