Symbolic machine learning improved MCFT model for punching shear resistance of FRP-reinforced concrete slabs
Author:
Publisher
Elsevier BV
Subject
Mechanics of Materials,Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering
Reference56 articles.
1. A new shear-flexible FRP-reinforced concrete slab element;Zhang;Compos. Struct.,2010
2. Development of machine learning models for reliable prediction of the punching shear strength of FRP-reinforced concrete slabs without shear reinforcements;Badra;Measurement,2022
3. Explainable machine learning-based model for failure mode identification of RC flat slabs without transverse reinforcement;Shen;Eng. Fail. Anal.,2022
4. A review on FRP-concrete hybrid sections for bridge applications;Zou;Compos. Struct.,2021
5. Damage assessment of RC flat slabs partially collapsed due to punching shear;Cosgun;Int. J. Civ. Eng.,2018
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. Punching shear strength of fiber-reinforced polymer concrete slabs: Database-driven assessment of parameters and prediction models;Engineering Structures;2024-09
2. Estimation and validation for fatigue properties of steels by symbolic regression;International Journal of Fatigue;2024-09
3. Machine Learning-Based Prediction Models for Punching Shear Strength of Fiber-Reinforced Polymer Reinforced Concrete Slabs Using a Gradient-Boosted Regression Tree;Materials;2024-08-09
4. ANN based fire resistance prediction of FRP-strengthened RC slabs with fireproof panel including air layer;Journal of Building Engineering;2024-08
5. Experimental studies and symbolic machine learning aided prediction model of the mechanical properties of recycled waste slurry micropowder mortar;Case Studies in Construction Materials;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