Integration of support vector regression and grey wolf optimization for estimating the ultimate bearing capacity in concrete-filled steel tube columns-Reference-Cited by-同舟云学术

Integration of support vector regression and grey wolf optimization for estimating the ultimate bearing capacity in concrete-filled steel tube columns

Published:2021-01-03 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Ngo Ngoc-Tri^ORCID,Le Hoang An,Pham Thi-Phuong-Trang

Funder

Vietnam Ministry of Education and Training

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-020-05605-z.pdf

Reference51 articles.

1. Han L-H, Li W, Bjorhovde R (2014) Developments and advanced applications of concrete-filled steel tubular (CFST) structures: members. J Constr Steel Res 100:211–228

2. Giakoumelis G, Lam D (2004) Axial capacity of circular concrete-filled tube columns. J Constr Steel Res 60:1049–1068

3. Le Hoang A, Fehling E (2017) Influence of steel fiber content and aspect ratio on the uniaxial tensile and compressive behavior of ultra high performance concrete. Constr Build Mater 153:790–806. https://doi.org/10.1016/j.conbuildmat.2017.07.130

4. De Nardin S, Debs A (2007) Axial load behaviour of concrete-filled steel tubular columns. Proc Inst Civ Eng-Struct Build 160:13–22

5. De Oliveira WLADN, De Cresce El Debs ALH, El Debs MK (2010) Evaluation of passive confinement in CFT columns. J Constr Steel Res 66(4):487–495

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