A swarm intelligence-based machine learning approach for predicting soil shear strength for road construction: a case study at Trung Luong National Expressway Project (Vietnam)-Reference-Cited by-同舟云学术

A swarm intelligence-based machine learning approach for predicting soil shear strength for road construction: a case study at Trung Luong National Expressway Project (Vietnam)

Published:2018-09-15 Issue:3 Volume:35 Page:955-965
ISSN:0177-0667
Container-title:Engineering with Computers
language:en
Short-container-title:Engineering with Computers

Author:

Tien Bui Dieu^ORCID,Hoang Nhat-Duc,Nhu Viet-Ha

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,General Engineering,Modeling and Simulation,Software

Link

http://link.springer.com/content/pdf/10.1007/s00366-018-0643-1.pdf

Reference49 articles.

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2. Sun S, Xu H (2007) Determining the shear strength of unsaturated silt. In: Schanz T (ed) Experimental unsaturated soil mechanics. Springer, Berlin, Heidelberg, pp 195–206

3. Vanapalli SK, Fredlund DG (2000) Comparison of different procedures to predict unsaturated soil shear strength. Adv Unsatur Geotech. https://doi.org/10.1061/40510(287)13

4. Pham BT, Son LH, Hoang T-A, Nguyen D-M, Tien Bui D (2018) Prediction of shear strength of soft soil using machine learning methods. CATENA 166:181–191. https://doi.org/10.1016/j.catena.2018.04.004

5. Das BM, Sobhan K (2013) Principles of geotechnical engineering. Cengage Learning (ISBN-10:1133108660)

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