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...
| Main Authors: | Khan, S., Khan, M.A., Zafar, A., Javed, M.F., Aslam, F., Musarat, M.A., Vatin, N.I. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.28911 / |
| Published: |
MDPI
2022
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121715454&doi=10.3390%2fma15010039&partnerID=40&md5=fa579baf45c28583aa70785da293bd1b http://eprints.utp.edu.my/28911/ |
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