Prediction of Rheological Parameters of Polymers Using the CatBoost Gradient Boosting Algorithm

The article discusses the problem of determining the rheological parameters of polymers from stress relaxation curves using the CatBoost machine learning algorithm. The model is trained on theoretical curves constructed using the nonlinear Maxwell–Gurevich equation. Comparisons are made with other m...

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Veröffentlicht in:	Polymer science. Series D, Glues and sealing materials Glues and sealing materials, 2024, Vol.17 (1), p.121-128
Hauptverfasser:	Chepurnenko, A. S., Kondratieva, T. N., Deberdeev, T. R., Akopyan, V. F., Avakov, A. A., Chepurnenko, V. S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Chemistry Chemistry and Materials Science Machine learning Parameters Polymer Sciences Polymers Rheological properties Stress relaxation
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Beschreibung
Zusammenfassung:	The article discusses the problem of determining the rheological parameters of polymers from stress relaxation curves using the CatBoost machine learning algorithm. The model is trained on theoretical curves constructed using the nonlinear Maxwell–Gurevich equation. Comparisons are made with other methods, including the classical algorithm, nonlinear optimization methods, and artificial neural networks.
ISSN:	1995-4212 1995-4220
DOI:	10.1134/S199542122370020X