Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes-Reference-Cited by-同舟云学术

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

Published:2019-01-10 Issue:4 Volume:43 Page:801-813
ISSN:0363-9061
Container-title:International Journal for Numerical and Analytical Methods in Geomechanics
language:en
Short-container-title:Int J Numer Anal Methods Geomech

Author:

Sun Yuantian¹²,Zhang Junfei²^ORCID,Li Guichen¹,Wang Yuhang³,Sun Junbo²,Jiang Chao⁴

Affiliation:

1. School of Mines, Key Laboratory of Deep Coal Resource Mining, Ministry of Education of China; China University of Mining and Technology; Xuzhou China

2. School of Civil, Environmental and Mining Engineering; The University of Western Australia; Perth Australia

3. Chinese Academy of Science; Institute of Information Engineering; Beijing China

4. School of Civil and Resources Engineering; University of Science and Technology Beijing; Beijing China

Funder

China Scholarship Council

National Natural Science Foundation of China

National Key Research and Development Program

Publisher

Wiley

Subject

Mechanics of Materials,Geotechnical Engineering and Engineering Geology,General Materials Science,Computational Mechanics

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/nag.2891/fullpdf

Reference48 articles.

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3. An evaluation method of ground improvement by jet grouting;Yoshitake;Tunn Undergr Sp Technol,2004

4. Support technologies for deep and complex roadways in underground coal mines: a review;Kang;Int J Coal Sci Technol,2014

5. Nonveiller E Grouting theory and practice 2013

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