AI-powered GUI for prediction of axial compression capacity in concrete-filled steel tube columns

被引：4
|
作者：
Asteris, Panagiotis G. [1 ]
Tsavdaridis, Konstantinos Daniel [2 ]
Lemonis, Minas E. [1 ]
Ferreira, Felipe Piana Vendramell [3 ]
Le, Tien-Thinh [4 ,5 ]
Gantes, Charis J. [6 ]
Formisano, Antonio [7 ]
机构：
[1] Computational Mechanics Laboratory, School of Pedagogical and Technological Education, Athens, Heraklion,GR 14121, Greece
[2] Department of Engineering, School of Science and Technology, City, University of London, Northampton Square, London,EC1V 0HB, United Kingdom
[3] Faculty of Civil Engineering, Federal University of Uberlândia, Campus Santa Mônica, Minas Gerais, Uberlândia, Brazil
[4] Faculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Yen Nghia, Ha Dong, Hanoi,12116, Viet Nam
[5] A & amp,A Green Phoenix Group JSC, Phenikaa Research and Technology Institute (PRATI), No.167 Hoang Ngan, Trung Hoa, Cau Giay, Hanoi,11313, Viet Nam
[6] Institute of Steel Structures, National Technical University of Athens, Athens,GR-15780, Greece
[7] Department of Structures for Engineering and Architecture, School of Polytechnic and Basic Sciences, University of Naples Federico II, P.Le V.Tecchio, Naples,80125, Italy
来源：
Neural Computing and Applications | 2024年 / 36卷 / 35期
关键词：
Rectangular concrete-filled steel tube (CFST); Finite element method (FEM); Load eccentricity; Artificial neural networks (ANNs); CFST; Long CFST; Ultimate load;
D O I：
10.1007/s00521-024-10405-w
中图分类号：
学科分类号：
摘要：
Graphical user interfaces
引用
收藏
页码：22429 / 22459
页数：30
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