Wang, ZhujunXing, YingmeiTao, XuyuanZeng, XianyiBruniaux, PascalXu, Zhenzhen2022-11-242022-11-242022Wang Z., Xing Y., Tao X., Zeng X., Bruniaux P., Xu Z., Knowledge-based personalized pattern design of legging for mass customization using support vector machine modelling. W: AUTEX 2022 : 21st World Textile Conference AUTEX 2022 - AUTEX Conference Proceedings, Lodz University of Technology Press, Lodz 2022, s. 326-329, ISBN 978-83-66741-75-1, doi: 10.34658/9788366741751.68.978-83-66741-75-1http://hdl.handle.net/11652/4502https://doi.org/10.34658/9788366741751.68In this study, we proposed a knowledge-based intelligent approach for pattern design of personalized garment toward mass customization using support vector machine modelling. This approach has been described and validated in the scenario of personalized legging design. The proposed models have been set up by learning from quantitative relationships between garment structure lines and controlling points, and then simulated for pattern parameters prediction. Finally, the performance of the presented approach was compared with the traditional grading method. From the experimental results, the design effect of the proposed approach is equivalent to the existing grading method. It indicates that our approach provides a feasible and valuable solution for promoting the personalized garment pattern design and facilitating the process of garment mass customization.enDla wszystkich w zakresie dozwolonego użytkuFair use conditiongarment pattern designmass customizationartificial intelligencemachine learningsupport vector machineprojektowanie wzorów odzieżymasowa personalizacjasztuczna inteligencjauczenie maszynowemaszyna wektorów pomocniczychartykuł - konferencjaLicencja PŁLUT License10.34658/9788366741751.68