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Support VectorMachines in PolymerScience: A Review :научное издание Malashin IvanTynchenko VadimGantimurov Andrei2025 год

Support Vector Machines in Polymer Science: A Review : научное издание
статья из журнала

Дополнительные ссылки: eLibrary
База данных: Каталог библиотеки СФУ
Библиографическое описание: Support Vector Machines in Polymer Science: A Review : научное издание / I. Malashin, V. Tynchenko, A. Gantimurov [et al.]. - Текст : непосредственный // Polymers. - 2025. - Т. 17, № 4. - P. 491. - ISSN 2073-4360, DOI 10.3390/polym17040491.
Аннотация: <jats:p>Polymer science, a discipline focusing on the synthesis, characterization, and application of macromolecules, has increasingly benefited from the adoption of machine learning (ML) techniques. Among these, Support Vector Machines (SVMs) stand out for their ability to handle nonlinear relationships and high-dimensional datasets, which are common in polymer research. This review explores the diverse applications of SVM in polymer science. Key examples include the prediction of mechanical and thermal properties, optimization of polymerization processes, and modeling of degradation mechanisms. The advantages of SVM are contrasted with its challenges, including computational cost, data dependency, and the need for hyperparameter tuning. Future opportunities, such as the development of polymer-specific kernels and integration with real-time manufacturing systems, are also discussed.</jats:p>
Год издания: 2025
Авторы: Malashin Ivan , Tynchenko Vadim , Gantimurov Andrei , Nelyub Vladimir , Borodulin Aleksei
Издательство: MDPI, Basel
Источник: Polymers
Выпуск: Т. 17, № 4
Номера страниц: 491
Держатель оригинала документа: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia, Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
Количество экземпляров:
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