Gaussian process model of water inflow prediction in tunnel construction and its engineering applications-Reference-Cited by-同舟云学术

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Gaussian process model of water inflow prediction in tunnel construction and its engineering applications

Published:2017-10 Issue: Volume:69 Page:155-161
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Li Shu-cai,He Peng^ORCID,Li Li-ping,Shi Shao-shuai,Zhang Qian-qing,Zhang Jian,Hu Jie

Funder

State Key Development Program for Basic Research of China

State Key Program of National Natural Science of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference43 articles.

1. A comparison between performance of support vector regression and artificial neural network in prediction of pipe burst rate in water distribution networks;Akbar;KSCE J. Civil Eng.,2014

2. Support vector machines: their use in geotechnical engineeirng as illustrated using seismic liquefaction data;Anthony;Comput. Geotech.,2007

3. Characterizing flow and transport in fractured geological media: a review;Berkowitz;Adv. Water Resour.,2002

4. Modeling non-linear displacement time series of geo-materials using evolutionary support vector machines;Feng;Int. J. Rock Mech. Min. Sci.,2004

5. Study on water inrush risk and early warning mechanism of karst tunnel;Ge,2010

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