The Application of Wavelet Neural Network in the Settlement Monitoring of Subway

YI Zhenghui (Tianjin Chengjian University, Tianjin 300384,China)
WANG Shuaimin (School of Geology and Geomatics, Tianjin Chengjian University, Tianjin 300384,China)
XU Yujing (College of Surveying Science and Engineering, Shandong University of Science and Technology, Qingdao 266510,China)
LIU Bei (School of Geology and Geomatics, Tianjin Chengjian University, Tianjin 300384,China)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 15, No 1: March 2017

The settlement monitoring of subway runs through the entire construction stage of subway. It is very important to predict the accurate settlement value for construction safety of subway. In this paper, the wavelet transform is used to denoise the settlement data. The auxiliary wavelet neural network, embedded wavelet neural network and single BP neural network are applied to predict the settlement of Tianjin subway. Compared with single BP neural network and auxiliary wavelet neural network, the embedded wavelet neural network model has a higher accuracy and better prediction effect. The embedded wavelet neural network is more valuable than the BP neural network model so it can be used in the prediction of subway settlement