Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Concrete filled steel tubes (CFSTs) show advantageous applications in the field of construction, especially for a high axial load capacity. The challenge in using such structure lies in the selection of many parameters constituting CFST, which necessitates defining complex relationships between the...

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Detalles Bibliográficos
Autores principales: Nguyen, Hung Quang, Ly, Hai-Bang, Tran, Van Quan, Nguyen, Thuy-Anh, Le, Tien-Thinh, Pham, Binh Thai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085075/
https://www.ncbi.nlm.nih.gov/pubmed/32156033
http://dx.doi.org/10.3390/ma13051205

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085075/
https://www.ncbi.nlm.nih.gov/pubmed/32156033
http://dx.doi.org/10.3390/ma13051205

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