A. S. Chepurnenko, T. N. Kondratieva, T. R. Deberdeev, V. F. Akopyan, A. A. Avakov, V. S. Chepurnenko
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引用次数: 0
Abstract
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.
期刊介绍：
Polymer Science, Series D publishes useful description of engineering developments that are related to the preparation and application of glues, compounds, sealing materials, and binding agents, articles on the adhesion theory, prediction of the strength of adhesive joints, methods for the control of their properties, synthesis, and methods of structural modeling of glued joints and constructions, original articles with new scientific results, analytical reviews of the modern state in the field.
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