DEFORMATION PREDICTION OF SUBWAY TUNNEL WITH NEURAL NETWORK METHOD
Pan Guorong 1,2)
1)Department of Surveying and Geomatics, Tongji University, Shanghai 2000922)Key Laboratory of Modern Engineering Surveying, SBSM, Shanghai 200092
Abstract On the basis of the advantage of the neural network method for processing nonlinear problem, some technological problems such as the election of technic parameteres may affect the network convergene in the prediction of tunnel deformation are analyzed. The method preventing exceed training and local optimization is presented.
Key words :
subway tunnel
deformation prediction
neural network
unitary
back-propagation
Received: 01 January 1900
Corresponding Authors:
Pan Guorong
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[2]
ZHOU Yang. Seismic Data Prediction Based on Regression Model of Nuclear Mixed Effects [J]. jgg, 2021, 41(9): 967-972.
[3]
TANG Jun,LI Yinjian,ZHONG Zhengyu,GAO Xin. Prediction Model of Ionospheric TEC by EOF and LSTM Neural Network [J]. jgg, 2021, 41(9): 911-915.
[4]
XUAN Jianhao,CHEN Zhiwei,ZHANG Xingfu,LIANG Chenghao,WU Bo. Combining GRACE and GRACE-FO to Derive Terrestrial Water Storage Changes in the Yangtze River Basin from 2002 to 2020 [J]. jgg, 2021, 41(9): 961-966.
[5]
HUANG Jiawei,LU Tieding,HE Xiaoxing,LI Wei. Short Term Prediction Model of Ionospheric TEC Based on Residual Correction of Prophet-Elman [J]. jgg, 2021, 41(8): 783-788.
[6]
LU Tieding,HUANG Jiawei,HE Xiaoxing,Lü Kaiyun. Short-Term Ionospheric TEC Prediction Using EWT-Elman Combination Model [J]. jgg, 2021, 41(7): 666-671.
[7]
PENG Zhao,SHAO Yongqian,LI He,LIU Lintao. Research on Seismic Detection Based on Machine Learning with Small Sample [J]. jgg, 2021, 41(7): 765-770.
[8]
LU Zhaoxing, Lü Zhifeng, LI Ting, ZHANG Jinsheng, YAO Yao. Forecasting of the Variable Geomagnetic Field Based on BP Neural Network [J]. jgg, 2021, 41(3): 229-233.
[9]
SHE Yawen, FU Guangyu. Estimation of Gravity Anomaly Data Based on Recurrent Neural Network [J]. jgg, 2021, 41(3): 234-237.
[10]
HUANG Wenxi, ZHU Fuying, ZHAI Dulin, LIN Jian, QING Yun, LI Xinxing, YANG Jian. Comparative Analysis of BP Neural Network and ARMA Model in Short-Term Prediction of Mid-Latitude TEC [J]. jgg, 2021, 41(3): 262-267.
[11]
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[12]
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[13]
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[14]
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[15]
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