Prediction of geology condition for slurry pressure balanced shield tunnel with super-large diameter by machine learning algorithms-Reference-Cited by-同舟云学术

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Prediction of geology condition for slurry pressure balanced shield tunnel with super-large diameter by machine learning algorithms

Published:2023-01 Issue: Volume:131 Page:104852
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Xu Deming,Wang Yusheng,Huang Jingqi,Liu Sijin,Xu Shujun,Zhou Kun

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference39 articles.

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4. Identifying characteristics of pipejacking parameters to assess geological conditions using optimisation algorithm-based support vector machines;Cheng;Tunn. Undergr. Space Technol.,2020

5. Practical selection of SVM parameters and noise estimation for SVM regression;Cherkassky;Neural Networks,2004

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