Prediction of compressive strength of geopolymer concrete by using ANN and GPR-Reference-Cited by-同舟云学术

Prediction of compressive strength of geopolymer concrete by using ANN and GPR

Published:2023-05-02 Issue:8 Volume:24 Page:2815-2823
ISSN:1563-0854
Container-title:Asian Journal of Civil Engineering
language:en
Short-container-title:Asian J Civ Eng

Author:

Verma Manvendra

Publisher

Springer Science and Business Media LLC

Subject

Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s42107-023-00676-4.pdf

Reference50 articles.

1. Abid, F., & Izeboudjen, N. (2020). Decision tree based system on chip for forest fires prediction. International Conference on Electrical Engineering. https://doi.org/10.1109/ICEE49691.2020.9249954

2. Ahmad, A., et al. (2022). Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques. Case Studies in Construction Materials. https://doi.org/10.1016/j.cscm.2021.e00840

3. Antony Jeyasehar, C., & Saravanan, G. (2013). Development of fly ash based geopolymer precast concrete elements. Asian Journal of Civil Engineering (BHRC), 14(4), 605–615.

4. Chindaprasirt, P., & Silva, P. D. (2012). Effect of SiO2 and Al2O3 on the setting and hardening of high calcium fly ash-based geopolymer systems. Journal of Material Science, 47, 4876–4883. https://doi.org/10.1007/s10853-012-6353-y

5. Chouksey, A., et al. (2022). An investigation on the effect of curing conditions on the mechanical and microstructural properties of the geopolymer concrete. Materials Research Express, 9(5), 55003. https://doi.org/10.1088/2053-1591/ac6be0

Cited by 10 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. Enhancing performance and sustainability of GGBFS-based self-compacting geopolymer concrete blended with coal bottom ash and metakaolin by using RSM modelling;Scientific Reports;2024-08-26

2. Assessment of ML techniques and suitability to predict the compressive strength of high-performance concrete (HPC);Asian Journal of Civil Engineering;2024-08-13

3. Advanced modeling techniques using hierarchical gaussian process regression in civil engineering;Asian Journal of Civil Engineering;2024-08-06

4. Investigation of mechanical behavior of mortar using slag as partial replacement of sand based on experimental and machine learning approaches;Asian Journal of Civil Engineering;2023-12-20

5. Length and width of low-light, concrete hairline crack detection and measurement using image processing method;Asian Journal of Civil Engineering;2023-12-19