Development of user-friendly kernel-based Gaussian process regression model for prediction of load-bearing capacity of square concrete-filled steel tubular members
A Machine Learning (ML) model based on Gaussian regression, using different kernel functions, is introduced in this paper to assess the load-carrying capacity of square concrete-filled steel tubular (CFST) columns. The input data used to develop the prediction model, which consists of 314 datasets i...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Materials and Structures 54(2), 59
2021
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| Subjects: | |
| Online Access: | https://link.springer.com/article/10.1617%2Fs11527-021-01646-5 https://dlib.phenikaa-uni.edu.vn/handle/PNK/1429 |
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