Тип публикации: статья из журнала
Год издания: 2024
Идентификатор DOI: 10.3390/polym16233368
Аннотация: <jats:p>The integration of machine learning (ML) into material manufacturing has driven advancements in optimizing biopolymer production processes. ML techniques, applied across various stages of biopolymer production, enable the analysis of complex data generated throughout production, identifying patterns and insights not easily Показать полностьюobserved through traditional methods. As sustainable alternatives to petrochemical-based plastics, biopolymers present unique challenges due to their reliance on variable bio-based feedstocks and complex processing conditions. This review systematically summarizes the current applications of ML techniques in biopolymer production, aiming to provide a comprehensive reference for future research while highlighting the potential of ML to enhance efficiency, reduce costs, and improve product quality. This review also shows the role of ML algorithms, including supervised, unsupervised, and deep learning algorithms, in optimizing biopolymer manufacturing processes.</jats:p>
Журнал: Polymers
Выпуск журнала: Т. 16, № 23
Номера страниц: 3368
ISSN журнала: 20734360
Место издания: Basel
Издатель: MDPI