Machine learning for optimal design of circular hollow section stainless steel stub columns: A comparative analysis with Eurocode 3 predictions-Reference-Cited by-同舟云学术

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Machine learning for optimal design of circular hollow section stainless steel stub columns: A comparative analysis with Eurocode 3 predictions

Published:2024-06 Issue: Volume:132 Page:107952
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Abarkan Ikram^ORCID,Rabi Musab,Ferreira Felipe Piana Vendramell,Shamass Rabee,Limbachiya Vireen^ORCID,Jweihan Yazeed S.^ORCID,Pinho Santos Luis Fernando^ORCID

Publisher

Elsevier BV

Reference120 articles.

1. Four-layer perceptron approach for strength prediction of UHPC;Abellán-García;Construct. Build. Mater.,2020

2. Experimental study of cold-formed ferritic stainless steel hollow sections;Afshan;J. Struct. Eng.,2013

3. The continuous strength method for structural stainless steel design;Afshan;Thin-Walled Struct.,2013

4. Reliability analysis of structural stainless steel design provisions;Afshan;J. Constr. Steel Res.,2015

5. Predictive models of behavior and capacity of frp reinforced concrete columns;Almomani;Journal of Applied Engineering Science,2023

Cited by 1 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. Experimental and numerical investigations on the bending capacity of cold-formed steel box headers;Scientific Reports;2024-07-10

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