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

页码：22429 / 22459

页数：30

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