Predicting split tensile strength in Portland and geopolymer concretes using machine learning algorithms: a comparative study
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41024-024-00485-5.pdf
Reference46 articles.
1. Luga E, Atis CD (2018) Optimization of heat cured fly ash/slag blend geopolymer mortars designed by Combined Design method: part 1. Constr Build Mater 178:393–404
2. Thomas BS (2018) Green concrete partially comprised of rice husk ash as a supplementary cementitious material–a comprehensive review. Renew Sustain Energy Rev 82:3913–3923
3. Zhang CY, Han R, Yu B, Wei YM (2018) Accounting process-related CO2 emissions from global cement production under Shared Socioeconomic pathways. J Clean Prod 184:451–465
4. Part WK, Ramli M, Cheah CB (2015) An overview on the influence of various factors on the properties of geopolymer concrete derived from industrial by-products. Constr Build Mater 77:370–395
5. Gogineni A, Rout MD, Shubham K (2024) Prediction of compressive strength of glass fiber-reinforced self-compacting concrete interpretable by machine learning algorithms. Asian J Civil Eng 25(2):2015–2032
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3