Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete-Reference-Cited by-同舟云学术

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

Published:2022-07 Issue:7 Volume:16 Page:928-945
ISSN:2095-2430
Container-title:Frontiers of Structural and Civil Engineering
language:en
Short-container-title:Front. Struct. Civ. Eng.

Author:

Tran Van Quan,Mai Hai-Van Thi,Nguyen Thuy-Anh,Ly Hai-Bang

Publisher

Springer Science and Business Media LLC

Subject

Architecture,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11709-022-0837-x.pdf

Reference110 articles.

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2. Fernandez-Gomez J, Landsberger G A. Evaluation of shrinkage prediction models for self-consolidating concrete. ACI Materials Journal, 2007, 104(5): 464

3. Skarendahl Å, Petersson Ö. Self-Compacting Concrete—State-of-the-Art report of RILEM Technical Committee 174-SCC. Cachan: RILEM Publications, 2000

4. Ramadan K Z, Haddad R H. Self-healing of overloaded self-compacting concrete of rigid pavement. European Journal of Environmental and Civil Engineering, 2017, 21(1): 63–77

5. Busari A A, Akinmusuru J O, Dahunsi B I O, Ogbiye A S, Okeniyi J O. Self-compacting concrete in pavement construction: Strength grouping of some selected brands of cements. Energy Procedia, 2017, 119: 863–869

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