Prediction of cement mortar strength by replacement of hydrated lime using RSM and ANN
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00577-6.pdf
Reference33 articles.
1. Adesina, P. A., & Olutoge, F. A. (2019). Structural properties of sustainable concrete developed using rice husk ash and hydrated lime. Journal of Building Engineering, 25, 100804. https://doi.org/10.1016/J.JOBE.2019.100804
2. Aravindh, M. D., Nakkeeran, G., Krishnaraj, L., & Arivusudar, N. (2022). Evaluation and optimization of lean waste in construction industry. Asian Journal of Civil Engineering, 1, 3. https://doi.org/10.1007/s42107-022-00453-9
3. Armaghani, D. J., & Asteris, P. G. (2021). A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Neural Computing and Applications, 33(9), 4501–4532. https://doi.org/10.1007/S00521-020-05244-4/TABLES/8
4. Barr, S., McCarter, W. J., & Suryanto, B. (2015). Bond-strength performance of hydraulic lime and natural cement mortared sandstone masonry. Construction and Building Materials, 84, 128–135. https://doi.org/10.1016/J.CONBUILDMAT.2015.03.016
5. Barreca, F., & Fichera, C. R. (2013). Use of olive stone as an additive in cement lime mortar to improve thermal insulation. Energy and Buildings, 62, 507–513. https://doi.org/10.1016/j.enbuild.2013.03.040
Cited by 18 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. Performance analysis of biochar and W. Robusta palm waste reinforced green mortar using response surface methodology and machine learning methods;Construction and Building Materials;2024-08
2. Kaolinite plastic binder in mortars: Rheological and mechanical properties;Powder Technology;2024-08
3. Predicting the compressive strength of carbon-enhanced cementitious composites using two-dimensional convolutional neural networks;Case Studies in Construction Materials;2024-07
4. Soft computing techniques for predicting the compressive strength properties of fly ash geopolymer concrete using regression-based machine learning approaches;Journal of Building Pathology and Rehabilitation;2024-06-19
5. Transient state analysis of rehabilitated RC beams using finite element modelling and prediction using an artificial neural network;Engineering Research Express;2024-05-13
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