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XGBoost-based prediction of residual properties of aged FRP composites

This repository contains preliminary code, datasets, and additional resources for an ongoing study on the long-term dynamic performance of a pultruded GFRP structure subjected to high humidity, moderate temperature, and mildly alkaline conditions. The work builds upon the framework proposed by Liu, Liu, and Feng (2022). Feedback and collaboration are welcome as results are being refined.

📂 Repository Structure

  • Active branch: main
    Used for stable releases.

📜 License and Attribution

This work is licensed under GPL-3.0 with additional attribution requirements.

📚 Citation

While our manuscript is under review, please cite this repository:

@software{frp-aging-xgboost,
  author = {Pereira, João Paulo D. de S.},
  title = {{XGBoost-based prediction of residual properties of aged FRP composites}},
  url = {https://github.com/pereira-joao-paulo/frp-aging-xgboost},
  year = {2025},
  note = {Article citation will be added upon publication}
}

💬 Questions or Feedback

We appreciate being informed of how this code is being used. For questions, feedback, or to share your case, feel free to reach out at jp_dias@id.uff.br.

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XGBoost-based prediction of residual properties of aged FRP composites

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