Comparative study on the performance of different machine learning techniques to predict the shear strength of RC deep beams: Model selection and industry implications

Author:

Le Nguyen Khuong,Thi Trinh Hoa,Nguyen Thanh T.,Nguyen Hoang D.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference54 articles.

1. ACI Committee 318. 2014. ACI 318-14 - Building Code Requirements for Structural Concrete.

2. Strength and behavior in shear of reinforced concrete deep beams under dynamic loading conditions;Adhikary;Nuclear Engineering and Design,2013

3. Assessing the accuracy of RC design code predictions through the use of artificial neural networks;Ahmad;International Journal of Advanced Structural Engineering,2018

4. Deep learning in the construction industry: A review of present status and future innovations;Akinosho;Journal of Building Engineering,2020

5. Mechanical behaviour and non-linear analysis of short beams using softened truss and direct strut & tie models;Bakir;Engineering Structures,2005

同舟云学术

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