Code for: An Optimized Machine Learning Approach for Reliable Design of Hybrid FRP–Steel–Concrete Tubular Columns
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| Formato: | Recurso digital |
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2026
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| _version_ | 1866902188405555200 |
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| author | Zhen, Luo Weiming, Tian |
| author_facet | Zhen, Luo Weiming, Tian |
| contents | <p>This record contains the full Python implementation used to reproduce the results reported in the manuscript “An Optimized Machine Learning Approach for Reliable Design of Hybrid FRP–Steel–Concrete Tubular Columns.” The archive includes scripts and/or notebooks for data preprocessing and cleaning, feature scaling, Bayesian hyperparameter optimization, model training, cross-validation, testing, SHAP-based interpretation, figure generation, and GUI deployment. The record also contains dependency specifications, trained model files, and example inputs needed to reproduce the reported outputs and figures.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19223309 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Code for: An Optimized Machine Learning Approach for Reliable Design of Hybrid FRP–Steel–Concrete Tubular Columns Zhen, Luo Weiming, Tian <p>This record contains the full Python implementation used to reproduce the results reported in the manuscript “An Optimized Machine Learning Approach for Reliable Design of Hybrid FRP–Steel–Concrete Tubular Columns.” The archive includes scripts and/or notebooks for data preprocessing and cleaning, feature scaling, Bayesian hyperparameter optimization, model training, cross-validation, testing, SHAP-based interpretation, figure generation, and GUI deployment. The record also contains dependency specifications, trained model files, and example inputs needed to reproduce the reported outputs and figures.</p> |
| title | Code for: An Optimized Machine Learning Approach for Reliable Design of Hybrid FRP–Steel–Concrete Tubular Columns |
| url | https://doi.org/10.5281/zenodo.19223309 |