Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector machine-Reference-Cited by-同舟云学术

Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector machine

Published:2018-06-04 Issue:1 Volume:13 Page:215-239
ISSN:2095-2430
Container-title:Frontiers of Structural and Civil Engineering
language:en
Short-container-title:Front. Struct. Civ. Eng.

Author:

Ghanizadeh Ali Reza,Abbaslou Hakime,Amlashi Amir Tavana,Alidoust Pourya

Publisher

Springer Science and Business Media LLC

Subject

Architecture,Civil and Structural Engineering

Link

http://link.springer.com/article/10.1007/s11709-018-0489-z/fulltext.html

Reference61 articles.

1. Kahl T W, Kauschinger J L, Perry E B. Repair, Evaluation, Maintenance, and Rehabilitation Research Program: Plastic Concrete Cutoff Walls for Earth Dams, DTIC Document, 1991

2. Hu LM, Gao DY, Li YZ, Song SQ. Analysis of the Influence of Long Curing Age on the Compressive Strength of Plastic Concrete. Advanced Materials Research, Trans Tech Publ, 2012, pp. 200–203

3. Zhang P, Guan Q Y, Li Q F. Mechanical Properties of Plastic Concrete Containing Bentonite, Research Journal of Applied Sciences. Engineering and Technology, 2013, 5(4): 1317–1322

4. Yu Y, Pu J, Ugai K. Study of mechanical properties of soil-cement mixture for a cut-off wall. Soil and Foundation, 1997, 37(4): 93–103

5. ICOLD. Filling materials for watertight cut off walls. Bulletin, International Committee of Large Dams, Paris, France, 1995

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessing the compressive and splitting tensile strength of self-compacting recycled coarse aggregate concrete using machine learning and statistical techniques;Materials Today Communications;2024-03

2. Optimization and characterization of hybrid bio-briquettes produced from the mixture of sawdust, sugarcane bagasse, and paddy straw;Environmental Science and Pollution Research;2024-02-01

3. Shear modulus prediction of landfill components using novel machine learners hybridized with forensic-based investigation optimization;Construction and Building Materials;2024-01

4. Mixed artificial intelligence models for compressive strength prediction and analysis of fly ash concrete;Advances in Engineering Software;2023-11

5. High-performance self-compacting concrete with recycled coarse aggregate: Soft-computing analysis of compressive strength;Journal of Building Engineering;2023-10