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A Multi-ObjectiveOptimization ofNeural Networks forPredicting thePhysical Propertiesof Textile PolymerComposite Materials Malashin IvanTynchenko VadimGantimurov Andrei2024 год

A Multi-Objective Optimization of Neural Networks for Predicting the Physical Properties of Textile Polymer Composite Materials
статья из журнала

Дополнительные ссылки: eLibrary
База данных: Каталог библиотеки СФУ
Библиографическое описание: A Multi-Objective Optimization of Neural Networks for Predicting the Physical Properties of Textile Polymer Composite Materials : научное издание / I. I. Malashin [et al.]. - Текст : непосредственный // Polymers. - 2024. - Т. 16, № 12. - P. 1752. - ISSN 2073-4360, DOI 10.3390/polym16121752.
Аннотация: <jats:p>This paper explores the application of multi-objective optimization techniques, including MOPSO, NSGA II, and SPEA2, to optimize the hyperparameters of artificial neural networks (ANNs) and support vector machines (SVMs) for predicting the physical properties of textile polymer composite materials (TPCMs). The optimization process utilizes data on the physical characteristics of the constituent fibers and fabrics used to manufacture these composites. By employing optimization algorithms, we aim to enhance the predictive accuracy of the ANN and SVM models, thereby facilitating the design and development of high-performance textile polymer composites. The effectiveness of the proposed approach is demonstrated through comparative analyses and validation experiments, highlighting its potential for optimizing complex material systems.</jats:p>
Год издания: 2024
Авторы: Malashin Ivan , Tynchenko Vadim , Gantimurov Andrei , Nelyub Vladimir , Borodulin Aleksei
Издательство: MDPI, Basel
Источник: Polymers
Выпуск: Т. 16, № 12
Номера страниц: 1752
Держатель оригинала документа: , Bauman Moscow State Technical University, , Far Eastern Federal University
Количество экземпляров:
Твёрдая копия издания отсутствует в фонде библиотеки

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