Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
http://link.springer.com/content/pdf/10.1007/s11356-021-12877-y.pdf
Reference40 articles.
1. Al-Shamiri AK, Kim JH, Yuan TF, Yoon YS (2019) Modeling the compressive strength of high-strength concrete: an extreme learning approach. Constr Build Mater 208:204–219. https://doi.org/10.1016/j.conbuildmat.2019.02.165
2. Al-Shamiri AK, Yuan TF, Kim JH (2020) Non-tuned machine learning approach for predicting the compressive strength of high-performance concrete. Materials (Basel) 13:1–15. https://doi.org/10.3390/ma13051023
3. Aljanabi QA, Chik Z, Allawi MF, el-Shafie AH, Ahmed AN, el-Shafie A (2018) Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment. Neural Comput & Applic 30:2459–2469. https://doi.org/10.1007/s00521-016-2807-5
4. Anandhi A, Srinivas V V., Nagesh Kumar D (2013) Impact of climate change on hydrometeorological variables in a River Basin in India for IPCC SRES scenarios. In: Climate Change Modeling, Mitigation, and Adaptation
5. Azimi-Pour M, Eskandari-Naddaf H, Pakzad A (2020) Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete. Constr Build Mater 230:117021. https://doi.org/10.1016/j.conbuildmat.2019.117021
Cited by 48 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. Comparative study on the prediction of the unconfined compressive strength of the one-part geopolymer stabilized soil by using different hybrid machine learning models;Case Studies in Construction Materials;2024-12
2. Prediction on the freeze-thaw resistance of a one-part geopolymer stabilized soil by using deep learning method;Case Studies in Construction Materials;2024-12
3. Prediction of the Unconfined Compressive Strength of a One-Part Geopolymer-Stabilized Soil Using Deep Learning Methods with Combined Real and Synthetic Data;Buildings;2024-09-13
4. Predicting slump for high‐performance concrete using decision tree and support vector regression approaches coupled with phasor particle swarm optimization algorithm;Structural Concrete;2024-08-11
5. Study on the deterioration of concrete performance in saline soil area under the combined effect of high low temperatures, chloride and sulfate salts;Cement and Concrete Composites;2024-07
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