Jiang Ping
Department of Civil Engineering, Shaoxing University, Huancheng, West Road No. 508, 312000, Shaoxing City, Zhejiang Province, China
ABSTRACT
Slope displacement is the external performance of slope stability, predicting slope displacement according to the original displacement monitoring data and predicting slope stability, which can effectively prevent the occurrence of landslide disaster. Slope displacement can be regard as the sum of trend item and random item, grey system G (1, 1) model can simulate the trend of the slope displacement time series and the wavelet neural network can predict the random variations of slope displacement. Based on the grey-wavelet neural network algorithm, prediction analysis of displacement was carried, the displacement prediction of Changchun west railway station foundation pit verify the accuracy and practicability of this method.
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Received: August 02, 2013;
Accepted: October 06, 2013;
Published: November 12, 2013
How to cite this article
Jiang Ping, 2013. Application of Grey Theory and Wavelet Neural Network in Slope Displacements Prediction. Journal of Applied Sciences, 13: 4764-4768.
DOI: 10.3923/jas.2013.4764.4768
URL: https://scialert.net/abstract/?doi=jas.2013.4764.4768
DOI: 10.3923/jas.2013.4764.4768
URL: https://scialert.net/abstract/?doi=jas.2013.4764.4768
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