Predicting the Ultimate Axial Capacity of Uniaxially Loaded CFST Columns Using Multiphysics Artificial Intelligence

The object of this research is concrete-filled steel tubes (CFST). The article aimed to develop a prediction Multiphysics model for the circular CFST column by using the Artificial Neural Network (ANN), the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Gene Expression Program (GEP). The data...

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Detalles Bibliográficos
Autores principales: Khan, Sangeen, Ali Khan, Mohsin, Zafar, Adeel, Javed, Muhammad Faisal, Aslam, Fahid, Musarat, Muhammad Ali, Vatin, Nikolai Ivanovich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746085/
https://www.ncbi.nlm.nih.gov/pubmed/35009186
http://dx.doi.org/10.3390/ma15010039

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746085/
https://www.ncbi.nlm.nih.gov/pubmed/35009186
http://dx.doi.org/10.3390/ma15010039

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