Using neural networks to predict the design load of cold-formed steel compression members-Reference-Cited by-同舟云学术

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Using neural networks to predict the design load of cold-formed steel compression members

Published:2002-07 Issue:7-10 Volume:33 Page:713-719
ISSN:0965-9978
Container-title:Advances in Engineering Software
language:en
Short-container-title:Advances in Engineering Software

Author:

El-Kassas E.M.A,Mackie R.I,El-Sheikh A.I

Publisher

Elsevier BV

Subject

General Engineering,Software

Reference15 articles.

1. Building design using cold-formed steel sections: value and benefit assessment of light steel framing in housing;Rogan,1998

2. Design of cold-formed steel members;Rhodes,1992

3. Building design using cold formed steel sections construction detailing and practice;Grubb,1997

4. Artificial neural networks: theory and applications;Patterson,1996

5. Fundamentals of artificial neural networks;Hassoun,1995

Cited by 11 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. Predicting restraining effects in CFS channels: A machine learning approach;STEEL COMPOS STRUCT;2024

2. Application of machine learning in cold-formed steel;Recent Trends in Cold-Formed Steel Construction;2024

3. Predicting the buckling behaviour of thin-walled structural elements using machine learning methods;Thin-Walled Structures;2023-03

4. Prediction of ultimate load carrying capacity of short cold-formed steel built-up lipped channel columns using machine learning approach;Sādhanā;2022-10-15

5. Analysis and Design Approaches of Cold-Formed Steel Members—A Review;Lecture Notes in Civil Engineering;2022-06-27

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